Automatic Regularization of TomoSAR Point Clouds for Buildings Using Neural Networks Article Swipe
Siyan Zhou
,
Yanlei Li
,
Fubo Zhang
,
Longyong Chen
,
Xiangxi Bu
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/s19173748
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/s19173748
Tomographic SAR (TomoSAR) is a remote sensing technique that extends the conventional two-dimensional (2-D) synthetic aperture radar (SAR) imaging principle to three-dimensional (3-D) imaging. It produces 3-D point clouds with unavoidable noise that seriously deteriorates the quality of 3-D imaging and the reconstruction of buildings over urban areas. However, existing methods for TomoSAR point cloud processing notably rely on data segmentation, which influences the processing efficiency and denoising performance to a large extent. Inspired by regression analysis, in this paper, we propose an automatic method using neural networks to regularize the 3-D building structures from TomoSAR point clouds. By changing the point heights, the surface points of a building are refined. The method has commendable performance on smoothening the building surface, and keeps a precise preservation of the building structure. Due to the regression mechanism, the method works in a high automation level, which avoids data segmentation and complex parameter adjustment. The experimental results demonstrate the effectiveness of our method to denoise and regularize TomoSAR point clouds for urban buildings.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s19173748
- https://www.mdpi.com/1424-8220/19/17/3748/pdf?version=1567137297
- OA Status
- gold
- Cited By
- 9
- References
- 48
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2970676859
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2970676859Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s19173748Digital Object Identifier
- Title
-
Automatic Regularization of TomoSAR Point Clouds for Buildings Using Neural NetworksWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-08-30Full publication date if available
- Authors
-
Siyan Zhou, Yanlei Li, Fubo Zhang, Longyong Chen, Xiangxi BuList of authors in order
- Landing page
-
https://doi.org/10.3390/s19173748Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/19/17/3748/pdf?version=1567137297Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/19/17/3748/pdf?version=1567137297Direct OA link when available
- Concepts
-
Point cloud, Regularization (linguistics), Segmentation, Computer science, Artificial intelligence, Computer vision, Synthetic aperture radar, Robustness (evolution), Artificial neural network, Chemistry, Gene, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
9Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2, 2023: 1, 2022: 1, 2021: 2Per-year citation counts (last 5 years)
- References (count)
-
48Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2970676859 |
|---|---|
| doi | https://doi.org/10.3390/s19173748 |
| ids.doi | https://doi.org/10.3390/s19173748 |
| ids.mag | 2970676859 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/31480211 |
| ids.openalex | https://openalex.org/W2970676859 |
| fwci | 1.58458419 |
| type | article |
| title | Automatic Regularization of TomoSAR Point Clouds for Buildings Using Neural Networks |
| biblio.issue | 17 |
| biblio.volume | 19 |
| biblio.last_page | 3748 |
| biblio.first_page | 3748 |
| topics[0].id | https://openalex.org/T10801 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9995999932289124 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2202 |
| topics[0].subfield.display_name | Aerospace Engineering |
| topics[0].display_name | Synthetic Aperture Radar (SAR) Applications and Techniques |
| topics[1].id | https://openalex.org/T11164 |
| topics[1].field.id | https://openalex.org/fields/23 |
| topics[1].field.display_name | Environmental Science |
| topics[1].score | 0.9962000250816345 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2305 |
| topics[1].subfield.display_name | Environmental Engineering |
| topics[1].display_name | Remote Sensing and LiDAR Applications |
| topics[2].id | https://openalex.org/T11038 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9925000071525574 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2202 |
| topics[2].subfield.display_name | Aerospace Engineering |
| topics[2].display_name | Advanced SAR Imaging Techniques |
| is_xpac | False |
| apc_list.value | 2400 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2598 |
| apc_paid.value | 2400 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2598 |
| concepts[0].id | https://openalex.org/C131979681 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8528614044189453 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1899648 |
| concepts[0].display_name | Point cloud |
| concepts[1].id | https://openalex.org/C2776135515 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6592252254486084 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q17143721 |
| concepts[1].display_name | Regularization (linguistics) |
| concepts[2].id | https://openalex.org/C89600930 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6334406137466431 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1423946 |
| concepts[2].display_name | Segmentation |
| concepts[3].id | https://openalex.org/C41008148 |
| concepts[3].level | 0 |
| concepts[3].score | 0.6275837421417236 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[3].display_name | Computer science |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.6214691400527954 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C31972630 |
| concepts[5].level | 1 |
| concepts[5].score | 0.6114254593849182 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[5].display_name | Computer vision |
| concepts[6].id | https://openalex.org/C87360688 |
| concepts[6].level | 2 |
| concepts[6].score | 0.5895599126815796 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q740686 |
| concepts[6].display_name | Synthetic aperture radar |
| concepts[7].id | https://openalex.org/C63479239 |
| concepts[7].level | 3 |
| concepts[7].score | 0.4540981352329254 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q7353546 |
| concepts[7].display_name | Robustness (evolution) |
| concepts[8].id | https://openalex.org/C50644808 |
| concepts[8].level | 2 |
| concepts[8].score | 0.44140374660491943 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[8].display_name | Artificial neural network |
| concepts[9].id | https://openalex.org/C185592680 |
| concepts[9].level | 0 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[9].display_name | Chemistry |
| concepts[10].id | https://openalex.org/C104317684 |
| concepts[10].level | 2 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q7187 |
| concepts[10].display_name | Gene |
| concepts[11].id | https://openalex.org/C55493867 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q7094 |
| concepts[11].display_name | Biochemistry |
| keywords[0].id | https://openalex.org/keywords/point-cloud |
| keywords[0].score | 0.8528614044189453 |
| keywords[0].display_name | Point cloud |
| keywords[1].id | https://openalex.org/keywords/regularization |
| keywords[1].score | 0.6592252254486084 |
| keywords[1].display_name | Regularization (linguistics) |
| keywords[2].id | https://openalex.org/keywords/segmentation |
| keywords[2].score | 0.6334406137466431 |
| keywords[2].display_name | Segmentation |
| keywords[3].id | https://openalex.org/keywords/computer-science |
| keywords[3].score | 0.6275837421417236 |
| keywords[3].display_name | Computer science |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.6214691400527954 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/computer-vision |
| keywords[5].score | 0.6114254593849182 |
| keywords[5].display_name | Computer vision |
| keywords[6].id | https://openalex.org/keywords/synthetic-aperture-radar |
| keywords[6].score | 0.5895599126815796 |
| keywords[6].display_name | Synthetic aperture radar |
| keywords[7].id | https://openalex.org/keywords/robustness |
| keywords[7].score | 0.4540981352329254 |
| keywords[7].display_name | Robustness (evolution) |
| keywords[8].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[8].score | 0.44140374660491943 |
| keywords[8].display_name | Artificial neural network |
| language | en |
| locations[0].id | doi:10.3390/s19173748 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S101949793 |
| locations[0].source.issn | 1424-8220 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1424-8220 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Sensors |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/1424-8220/19/17/3748/pdf?version=1567137297 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Sensors |
| locations[0].landing_page_url | https://doi.org/10.3390/s19173748 |
| locations[1].id | pmid:31480211 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Sensors (Basel, Switzerland) |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/31480211 |
| locations[2].id | pmh:oai:doaj.org/article:7f9f00bab22a46f287b936bae4b4d45c |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | cc-by-sa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Sensors, Vol 19, Iss 17, p 3748 (2019) |
| locations[2].landing_page_url | https://doaj.org/article/7f9f00bab22a46f287b936bae4b4d45c |
| locations[3].id | pmh:oai:mdpi.com:/1424-8220/19/17/3748/ |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S4306400947 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | True |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | MDPI (MDPI AG) |
| locations[3].source.host_organization | https://openalex.org/I4210097602 |
| locations[3].source.host_organization_name | Multidisciplinary Digital Publishing Institute (Switzerland) |
| locations[3].source.host_organization_lineage | https://openalex.org/I4210097602 |
| locations[3].license | cc-by |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/cc-by |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Sensors |
| locations[3].landing_page_url | http://dx.doi.org/10.3390/s19173748 |
| locations[4].id | pmh:oai:pubmedcentral.nih.gov:6749584 |
| locations[4].is_oa | True |
| locations[4].source.id | https://openalex.org/S2764455111 |
| locations[4].source.issn | |
| locations[4].source.type | repository |
| locations[4].source.is_oa | False |
| locations[4].source.issn_l | |
| locations[4].source.is_core | False |
| locations[4].source.is_in_doaj | False |
| locations[4].source.display_name | PubMed Central |
| locations[4].source.host_organization | https://openalex.org/I1299303238 |
| locations[4].source.host_organization_name | National Institutes of Health |
| locations[4].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[4].license | other-oa |
| locations[4].pdf_url | |
| locations[4].version | submittedVersion |
| locations[4].raw_type | Text |
| locations[4].license_id | https://openalex.org/licenses/other-oa |
| locations[4].is_accepted | False |
| locations[4].is_published | False |
| locations[4].raw_source_name | Sensors (Basel) |
| locations[4].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/6749584 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5079762345 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Siyan Zhou |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210165038 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[0].affiliations[1].raw_affiliation_string | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China |
| authorships[0].institutions[0].id | https://openalex.org/I19820366 |
| authorships[0].institutions[0].ror | https://ror.org/034t30j35 |
| authorships[0].institutions[0].type | government |
| authorships[0].institutions[0].lineage | https://openalex.org/I19820366 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Chinese Academy of Sciences |
| authorships[0].institutions[1].id | https://openalex.org/I4210110458 |
| authorships[0].institutions[1].ror | https://ror.org/01z143507 |
| authorships[0].institutions[1].type | facility |
| authorships[0].institutions[1].lineage | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[0].institutions[1].country_code | CN |
| authorships[0].institutions[1].display_name | Institute of Electronics |
| authorships[0].institutions[2].id | https://openalex.org/I4210165038 |
| authorships[0].institutions[2].ror | https://ror.org/05qbk4x57 |
| authorships[0].institutions[2].type | education |
| authorships[0].institutions[2].lineage | https://openalex.org/I19820366, https://openalex.org/I4210165038 |
| authorships[0].institutions[2].country_code | CN |
| authorships[0].institutions[2].display_name | University of Chinese Academy of Sciences |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Siyan Zhou |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China, School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China |
| authorships[1].author.id | https://openalex.org/A5100648601 |
| authorships[1].author.orcid | https://orcid.org/0009-0004-9473-6218 |
| authorships[1].author.display_name | Yanlei Li |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[1].affiliations[0].raw_affiliation_string | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I4210165038 |
| authorships[1].affiliations[1].raw_affiliation_string | School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China |
| authorships[1].institutions[0].id | https://openalex.org/I19820366 |
| authorships[1].institutions[0].ror | https://ror.org/034t30j35 |
| authorships[1].institutions[0].type | government |
| authorships[1].institutions[0].lineage | https://openalex.org/I19820366 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Chinese Academy of Sciences |
| authorships[1].institutions[1].id | https://openalex.org/I4210110458 |
| authorships[1].institutions[1].ror | https://ror.org/01z143507 |
| authorships[1].institutions[1].type | facility |
| authorships[1].institutions[1].lineage | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[1].institutions[1].country_code | CN |
| authorships[1].institutions[1].display_name | Institute of Electronics |
| authorships[1].institutions[2].id | https://openalex.org/I4210165038 |
| authorships[1].institutions[2].ror | https://ror.org/05qbk4x57 |
| authorships[1].institutions[2].type | education |
| authorships[1].institutions[2].lineage | https://openalex.org/I19820366, https://openalex.org/I4210165038 |
| authorships[1].institutions[2].country_code | CN |
| authorships[1].institutions[2].display_name | University of Chinese Academy of Sciences |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Yanlei Li |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China, School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China |
| authorships[2].author.id | https://openalex.org/A5006052289 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-3179-052X |
| authorships[2].author.display_name | Fubo Zhang |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[2].affiliations[0].raw_affiliation_string | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China |
| authorships[2].institutions[0].id | https://openalex.org/I19820366 |
| authorships[2].institutions[0].ror | https://ror.org/034t30j35 |
| authorships[2].institutions[0].type | government |
| authorships[2].institutions[0].lineage | https://openalex.org/I19820366 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Chinese Academy of Sciences |
| authorships[2].institutions[1].id | https://openalex.org/I4210110458 |
| authorships[2].institutions[1].ror | https://ror.org/01z143507 |
| authorships[2].institutions[1].type | facility |
| authorships[2].institutions[1].lineage | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[2].institutions[1].country_code | CN |
| authorships[2].institutions[1].display_name | Institute of Electronics |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Fubo Zhang |
| authorships[2].is_corresponding | True |
| authorships[2].raw_affiliation_strings | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China |
| authorships[3].author.id | https://openalex.org/A5025884811 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-3939-6973 |
| authorships[3].author.display_name | Longyong Chen |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210165038 |
| authorships[3].affiliations[0].raw_affiliation_string | School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China |
| authorships[3].affiliations[1].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[3].affiliations[1].raw_affiliation_string | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China |
| authorships[3].institutions[0].id | https://openalex.org/I19820366 |
| authorships[3].institutions[0].ror | https://ror.org/034t30j35 |
| authorships[3].institutions[0].type | government |
| authorships[3].institutions[0].lineage | https://openalex.org/I19820366 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | Chinese Academy of Sciences |
| authorships[3].institutions[1].id | https://openalex.org/I4210110458 |
| authorships[3].institutions[1].ror | https://ror.org/01z143507 |
| authorships[3].institutions[1].type | facility |
| authorships[3].institutions[1].lineage | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[3].institutions[1].country_code | CN |
| authorships[3].institutions[1].display_name | Institute of Electronics |
| authorships[3].institutions[2].id | https://openalex.org/I4210165038 |
| authorships[3].institutions[2].ror | https://ror.org/05qbk4x57 |
| authorships[3].institutions[2].type | education |
| authorships[3].institutions[2].lineage | https://openalex.org/I19820366, https://openalex.org/I4210165038 |
| authorships[3].institutions[2].country_code | CN |
| authorships[3].institutions[2].display_name | University of Chinese Academy of Sciences |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Longyong Chen |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China, School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China |
| authorships[4].author.id | https://openalex.org/A5102858257 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-4786-3386 |
| authorships[4].author.display_name | Xiangxi Bu |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210165038 |
| authorships[4].affiliations[0].raw_affiliation_string | School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[4].affiliations[1].raw_affiliation_string | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China |
| authorships[4].institutions[0].id | https://openalex.org/I19820366 |
| authorships[4].institutions[0].ror | https://ror.org/034t30j35 |
| authorships[4].institutions[0].type | government |
| authorships[4].institutions[0].lineage | https://openalex.org/I19820366 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | Chinese Academy of Sciences |
| authorships[4].institutions[1].id | https://openalex.org/I4210110458 |
| authorships[4].institutions[1].ror | https://ror.org/01z143507 |
| authorships[4].institutions[1].type | facility |
| authorships[4].institutions[1].lineage | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| authorships[4].institutions[1].country_code | CN |
| authorships[4].institutions[1].display_name | Institute of Electronics |
| authorships[4].institutions[2].id | https://openalex.org/I4210165038 |
| authorships[4].institutions[2].ror | https://ror.org/05qbk4x57 |
| authorships[4].institutions[2].type | education |
| authorships[4].institutions[2].lineage | https://openalex.org/I19820366, https://openalex.org/I4210165038 |
| authorships[4].institutions[2].country_code | CN |
| authorships[4].institutions[2].display_name | University of Chinese Academy of Sciences |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Xiangxi Bu |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China, School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/1424-8220/19/17/3748/pdf?version=1567137297 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Automatic Regularization of TomoSAR Point Clouds for Buildings Using Neural Networks |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10801 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9995999932289124 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2202 |
| primary_topic.subfield.display_name | Aerospace Engineering |
| primary_topic.display_name | Synthetic Aperture Radar (SAR) Applications and Techniques |
| related_works | https://openalex.org/W3016928466, https://openalex.org/W4389574804, https://openalex.org/W2936725271, https://openalex.org/W3150655618, https://openalex.org/W2295788148, https://openalex.org/W1578717197, https://openalex.org/W3108295644, https://openalex.org/W2626737336, https://openalex.org/W2005998065, https://openalex.org/W2114282491 |
| cited_by_count | 9 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 2 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 1 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 1 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 2 |
| counts_by_year[5].year | 2020 |
| counts_by_year[5].cited_by_count | 1 |
| counts_by_year[6].year | 2019 |
| counts_by_year[6].cited_by_count | 1 |
| locations_count | 5 |
| best_oa_location.id | doi:10.3390/s19173748 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S101949793 |
| best_oa_location.source.issn | 1424-8220 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1424-8220 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Sensors |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/1424-8220/19/17/3748/pdf?version=1567137297 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Sensors |
| best_oa_location.landing_page_url | https://doi.org/10.3390/s19173748 |
| primary_location.id | doi:10.3390/s19173748 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S101949793 |
| primary_location.source.issn | 1424-8220 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1424-8220 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Sensors |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/1424-8220/19/17/3748/pdf?version=1567137297 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Sensors |
| primary_location.landing_page_url | https://doi.org/10.3390/s19173748 |
| publication_date | 2019-08-30 |
| publication_year | 2019 |
| referenced_works | https://openalex.org/W214427144, https://openalex.org/W2157228516, https://openalex.org/W2146328153, https://openalex.org/W2001587991, https://openalex.org/W2118005898, https://openalex.org/W2011855708, https://openalex.org/W1992746498, https://openalex.org/W6757251619, https://openalex.org/W6718512924, https://openalex.org/W2048289234, https://openalex.org/W2085261163, https://openalex.org/W2130017587, https://openalex.org/W1519594923, https://openalex.org/W2091446142, https://openalex.org/W2014471961, https://openalex.org/W2153319319, https://openalex.org/W6757915590, https://openalex.org/W2795798402, https://openalex.org/W2075165966, https://openalex.org/W2054585327, https://openalex.org/W6641664353, https://openalex.org/W2122132455, https://openalex.org/W2253347938, https://openalex.org/W2288642056, https://openalex.org/W2414349585, https://openalex.org/W2764034829, https://openalex.org/W2549994478, https://openalex.org/W1644641054, https://openalex.org/W1955462214, https://openalex.org/W2254644702, https://openalex.org/W2963021451, https://openalex.org/W2211722331, https://openalex.org/W2962731536, https://openalex.org/W6640300118, https://openalex.org/W2555254696, https://openalex.org/W2950642167, https://openalex.org/W2624503621, https://openalex.org/W2898605096, https://openalex.org/W2619516334, https://openalex.org/W2963121255, https://openalex.org/W1920022804, https://openalex.org/W1966282540, https://openalex.org/W1662382123, https://openalex.org/W2952789225, https://openalex.org/W2782522152, https://openalex.org/W2907282259, https://openalex.org/W2910170141, https://openalex.org/W2240571584 |
| referenced_works_count | 48 |
| abstract_inverted_index.a | 4, 70, 107, 123, 139 |
| abstract_inverted_index.By | 98 |
| abstract_inverted_index.It | 24 |
| abstract_inverted_index.an | 82 |
| abstract_inverted_index.by | 74 |
| abstract_inverted_index.in | 77, 138 |
| abstract_inverted_index.is | 3 |
| abstract_inverted_index.of | 37, 43, 106, 126, 157 |
| abstract_inverted_index.on | 58, 116 |
| abstract_inverted_index.to | 20, 69, 88, 131, 160 |
| abstract_inverted_index.we | 80 |
| abstract_inverted_index.3-D | 26, 38, 91 |
| abstract_inverted_index.Due | 130 |
| abstract_inverted_index.SAR | 1 |
| abstract_inverted_index.The | 111, 151 |
| abstract_inverted_index.and | 40, 66, 121, 147, 162 |
| abstract_inverted_index.are | 109 |
| abstract_inverted_index.for | 51, 167 |
| abstract_inverted_index.has | 113 |
| abstract_inverted_index.our | 158 |
| abstract_inverted_index.the | 10, 35, 41, 63, 90, 100, 103, 118, 127, 132, 135, 155 |
| abstract_inverted_index.data | 59, 145 |
| abstract_inverted_index.from | 94 |
| abstract_inverted_index.high | 140 |
| abstract_inverted_index.over | 45 |
| abstract_inverted_index.rely | 57 |
| abstract_inverted_index.that | 8, 32 |
| abstract_inverted_index.this | 78 |
| abstract_inverted_index.with | 29 |
| abstract_inverted_index.(2-D) | 13 |
| abstract_inverted_index.(3-D) | 22 |
| abstract_inverted_index.(SAR) | 17 |
| abstract_inverted_index.cloud | 54 |
| abstract_inverted_index.keeps | 122 |
| abstract_inverted_index.large | 71 |
| abstract_inverted_index.noise | 31 |
| abstract_inverted_index.point | 27, 53, 96, 101, 165 |
| abstract_inverted_index.radar | 16 |
| abstract_inverted_index.urban | 46, 168 |
| abstract_inverted_index.using | 85 |
| abstract_inverted_index.which | 61, 143 |
| abstract_inverted_index.works | 137 |
| abstract_inverted_index.areas. | 47 |
| abstract_inverted_index.avoids | 144 |
| abstract_inverted_index.clouds | 28, 166 |
| abstract_inverted_index.level, | 142 |
| abstract_inverted_index.method | 84, 112, 136, 159 |
| abstract_inverted_index.neural | 86 |
| abstract_inverted_index.paper, | 79 |
| abstract_inverted_index.points | 105 |
| abstract_inverted_index.remote | 5 |
| abstract_inverted_index.TomoSAR | 52, 95, 164 |
| abstract_inverted_index.clouds. | 97 |
| abstract_inverted_index.complex | 148 |
| abstract_inverted_index.denoise | 161 |
| abstract_inverted_index.extends | 9 |
| abstract_inverted_index.extent. | 72 |
| abstract_inverted_index.imaging | 18, 39 |
| abstract_inverted_index.methods | 50 |
| abstract_inverted_index.notably | 56 |
| abstract_inverted_index.precise | 124 |
| abstract_inverted_index.propose | 81 |
| abstract_inverted_index.quality | 36 |
| abstract_inverted_index.results | 153 |
| abstract_inverted_index.sensing | 6 |
| abstract_inverted_index.surface | 104 |
| abstract_inverted_index.However, | 48 |
| abstract_inverted_index.Inspired | 73 |
| abstract_inverted_index.aperture | 15 |
| abstract_inverted_index.building | 92, 108, 119, 128 |
| abstract_inverted_index.changing | 99 |
| abstract_inverted_index.existing | 49 |
| abstract_inverted_index.heights, | 102 |
| abstract_inverted_index.imaging. | 23 |
| abstract_inverted_index.networks | 87 |
| abstract_inverted_index.produces | 25 |
| abstract_inverted_index.refined. | 110 |
| abstract_inverted_index.surface, | 120 |
| abstract_inverted_index.(TomoSAR) | 2 |
| abstract_inverted_index.analysis, | 76 |
| abstract_inverted_index.automatic | 83 |
| abstract_inverted_index.buildings | 44 |
| abstract_inverted_index.denoising | 67 |
| abstract_inverted_index.parameter | 149 |
| abstract_inverted_index.principle | 19 |
| abstract_inverted_index.seriously | 33 |
| abstract_inverted_index.synthetic | 14 |
| abstract_inverted_index.technique | 7 |
| abstract_inverted_index.automation | 141 |
| abstract_inverted_index.buildings. | 169 |
| abstract_inverted_index.efficiency | 65 |
| abstract_inverted_index.influences | 62 |
| abstract_inverted_index.mechanism, | 134 |
| abstract_inverted_index.processing | 55, 64 |
| abstract_inverted_index.regression | 75, 133 |
| abstract_inverted_index.regularize | 89, 163 |
| abstract_inverted_index.structure. | 129 |
| abstract_inverted_index.structures | 93 |
| abstract_inverted_index.Tomographic | 0 |
| abstract_inverted_index.adjustment. | 150 |
| abstract_inverted_index.commendable | 114 |
| abstract_inverted_index.demonstrate | 154 |
| abstract_inverted_index.performance | 68, 115 |
| abstract_inverted_index.smoothening | 117 |
| abstract_inverted_index.unavoidable | 30 |
| abstract_inverted_index.conventional | 11 |
| abstract_inverted_index.deteriorates | 34 |
| abstract_inverted_index.experimental | 152 |
| abstract_inverted_index.preservation | 125 |
| abstract_inverted_index.segmentation | 146 |
| abstract_inverted_index.effectiveness | 156 |
| abstract_inverted_index.segmentation, | 60 |
| abstract_inverted_index.reconstruction | 42 |
| abstract_inverted_index.two-dimensional | 12 |
| abstract_inverted_index.three-dimensional | 21 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5006052289 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210110458 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.8600000143051147 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.87898053 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |