Efficient and Consumer-Centered Item Detection and Classification with a Multicamera Network at High Ranges Article Swipe
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/s21144818
In the EU project SHAREWORK, methods are developed that allow humans and robots to collaborate in an industrial environment. One of the major contributions is a framework for task planning coupled with automated item detection and localization. In this work, we present the methods used for detecting and classifying items on the shop floor. Important in the context of SHAREWORK is the user-friendliness of the methodology. Thus, we renounce heavy-learning-based methods in favor of unsupervised segmentation coupled with lenient machine learning methods for classification. Our algorithm is a combination of established methods adjusted for fast and reliable item detection at high ranges of up to eight meters. In this work, we present the full pipeline from calibration, over segmentation to item classification in the industrial context. The pipeline is validated on a shop floor of 40 sqm and with up to nine different items and assemblies, reaching a mean accuracy of 84% at 0.85 Hz.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s21144818
- https://www.mdpi.com/1424-8220/21/14/4818/pdf?version=1626317957
- OA Status
- gold
- Cited By
- 4
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3183839916
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3183839916Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s21144818Digital Object Identifier
- Title
-
Efficient and Consumer-Centered Item Detection and Classification with a Multicamera Network at High RangesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-07-14Full publication date if available
- Authors
-
Nils Mandischer, Tobias Huhn, Mathias Hüsing, Burkhard CorvesList of authors in order
- Landing page
-
https://doi.org/10.3390/s21144818Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/21/14/4818/pdf?version=1626317957Direct 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/1424-8220/21/14/4818/pdf?version=1626317957Direct OA link when available
- Concepts
-
Pipeline (software), Context (archaeology), Computer science, Segmentation, Task (project management), Artificial intelligence, Machine learning, Robot, Object detection, Engineering, Paleontology, Systems engineering, Biology, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2023: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
24Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3183839916 |
|---|---|
| doi | https://doi.org/10.3390/s21144818 |
| ids.doi | https://doi.org/10.3390/s21144818 |
| ids.mag | 3183839916 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/34300558 |
| ids.openalex | https://openalex.org/W3183839916 |
| fwci | 0.92170078 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D000465 |
| mesh[0].is_major_topic | True |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Algorithms |
| mesh[1].qualifier_ui | |
| mesh[1].descriptor_ui | D006801 |
| mesh[1].is_major_topic | False |
| mesh[1].qualifier_name | |
| mesh[1].descriptor_name | Humans |
| mesh[2].qualifier_ui | |
| mesh[2].descriptor_ui | D000069550 |
| mesh[2].is_major_topic | True |
| mesh[2].qualifier_name | |
| mesh[2].descriptor_name | Machine Learning |
| mesh[3].qualifier_ui | |
| mesh[3].descriptor_ui | D000465 |
| mesh[3].is_major_topic | True |
| mesh[3].qualifier_name | |
| mesh[3].descriptor_name | Algorithms |
| mesh[4].qualifier_ui | |
| mesh[4].descriptor_ui | D006801 |
| mesh[4].is_major_topic | False |
| mesh[4].qualifier_name | |
| mesh[4].descriptor_name | Humans |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D000069550 |
| mesh[5].is_major_topic | True |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Machine Learning |
| type | article |
| title | Efficient and Consumer-Centered Item Detection and Classification with a Multicamera Network at High Ranges |
| biblio.issue | 14 |
| biblio.volume | 21 |
| biblio.last_page | 4818 |
| biblio.first_page | 4818 |
| topics[0].id | https://openalex.org/T10191 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9983000159263611 |
| 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 | Robotics and Sensor-Based Localization |
| topics[1].id | https://openalex.org/T10036 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.998199999332428 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1707 |
| topics[1].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[1].display_name | Advanced Neural Network Applications |
| topics[2].id | https://openalex.org/T11605 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9961000084877014 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1707 |
| topics[2].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[2].display_name | Visual Attention and Saliency Detection |
| 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/C43521106 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8035290241241455 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q2165493 |
| concepts[0].display_name | Pipeline (software) |
| concepts[1].id | https://openalex.org/C2779343474 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7527156472206116 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q3109175 |
| concepts[1].display_name | Context (archaeology) |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.7342015504837036 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C89600930 |
| concepts[3].level | 2 |
| concepts[3].score | 0.7031566500663757 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1423946 |
| concepts[3].display_name | Segmentation |
| concepts[4].id | https://openalex.org/C2780451532 |
| concepts[4].level | 2 |
| concepts[4].score | 0.660456657409668 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q759676 |
| concepts[4].display_name | Task (project management) |
| concepts[5].id | https://openalex.org/C154945302 |
| concepts[5].level | 1 |
| concepts[5].score | 0.6532813310623169 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[5].display_name | Artificial intelligence |
| concepts[6].id | https://openalex.org/C119857082 |
| concepts[6].level | 1 |
| concepts[6].score | 0.5093303918838501 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[6].display_name | Machine learning |
| concepts[7].id | https://openalex.org/C90509273 |
| concepts[7].level | 2 |
| concepts[7].score | 0.46393564343452454 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11012 |
| concepts[7].display_name | Robot |
| concepts[8].id | https://openalex.org/C2776151529 |
| concepts[8].level | 3 |
| concepts[8].score | 0.426448255777359 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q3045304 |
| concepts[8].display_name | Object detection |
| concepts[9].id | https://openalex.org/C127413603 |
| concepts[9].level | 0 |
| concepts[9].score | 0.12562283873558044 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[9].display_name | Engineering |
| concepts[10].id | https://openalex.org/C151730666 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q7205 |
| concepts[10].display_name | Paleontology |
| concepts[11].id | https://openalex.org/C201995342 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q682496 |
| concepts[11].display_name | Systems engineering |
| concepts[12].id | https://openalex.org/C86803240 |
| concepts[12].level | 0 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[12].display_name | Biology |
| concepts[13].id | https://openalex.org/C199360897 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[13].display_name | Programming language |
| keywords[0].id | https://openalex.org/keywords/pipeline |
| keywords[0].score | 0.8035290241241455 |
| keywords[0].display_name | Pipeline (software) |
| keywords[1].id | https://openalex.org/keywords/context |
| keywords[1].score | 0.7527156472206116 |
| keywords[1].display_name | Context (archaeology) |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.7342015504837036 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/segmentation |
| keywords[3].score | 0.7031566500663757 |
| keywords[3].display_name | Segmentation |
| keywords[4].id | https://openalex.org/keywords/task |
| keywords[4].score | 0.660456657409668 |
| keywords[4].display_name | Task (project management) |
| keywords[5].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[5].score | 0.6532813310623169 |
| keywords[5].display_name | Artificial intelligence |
| keywords[6].id | https://openalex.org/keywords/machine-learning |
| keywords[6].score | 0.5093303918838501 |
| keywords[6].display_name | Machine learning |
| keywords[7].id | https://openalex.org/keywords/robot |
| keywords[7].score | 0.46393564343452454 |
| keywords[7].display_name | Robot |
| keywords[8].id | https://openalex.org/keywords/object-detection |
| keywords[8].score | 0.426448255777359 |
| keywords[8].display_name | Object detection |
| keywords[9].id | https://openalex.org/keywords/engineering |
| keywords[9].score | 0.12562283873558044 |
| keywords[9].display_name | Engineering |
| language | en |
| locations[0].id | doi:10.3390/s21144818 |
| 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/1424-8220/21/14/4818/pdf?version=1626317957 |
| 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/s21144818 |
| locations[1].id | pmid:34300558 |
| 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/34300558 |
| locations[2].id | pmh:oai:doaj.org/article:6e9019bde3c44e879aa46561f498623b |
| 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 21, Iss 14, p 4818 (2021) |
| locations[2].landing_page_url | https://doaj.org/article/6e9019bde3c44e879aa46561f498623b |
| locations[3].id | pmh:oai:mdpi.com:/1424-8220/21/14/4818/ |
| 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; Volume 21; Issue 14; Pages: 4818 |
| locations[3].landing_page_url | https://dx.doi.org/10.3390/s21144818 |
| locations[4].id | pmh:oai:pubmedcentral.nih.gov:8309894 |
| 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/8309894 |
| locations[5].id | pmh:oai:uni-augsburg.opus-bayern.de:117880 |
| locations[5].is_oa | True |
| locations[5].source.id | https://openalex.org/S4306400930 |
| locations[5].source.issn | |
| locations[5].source.type | repository |
| locations[5].source.is_oa | False |
| locations[5].source.issn_l | |
| locations[5].source.is_core | False |
| locations[5].source.is_in_doaj | False |
| locations[5].source.display_name | OPUS (Augsburg University) |
| locations[5].source.host_organization | https://openalex.org/I119916105 |
| locations[5].source.host_organization_name | Augsburg University |
| locations[5].source.host_organization_lineage | https://openalex.org/I119916105 |
| locations[5].license | cc-by |
| locations[5].pdf_url | |
| locations[5].version | submittedVersion |
| locations[5].raw_type | doc-type:article |
| locations[5].license_id | https://openalex.org/licenses/cc-by |
| locations[5].is_accepted | False |
| locations[5].is_published | False |
| locations[5].raw_source_name | |
| locations[5].landing_page_url | https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/117880 |
| locations[6].id | pmh:oai:zenodo.org:5547209 |
| locations[6].is_oa | True |
| locations[6].source.id | https://openalex.org/S4306400562 |
| locations[6].source.issn | |
| locations[6].source.type | repository |
| locations[6].source.is_oa | True |
| locations[6].source.issn_l | |
| locations[6].source.is_core | False |
| locations[6].source.is_in_doaj | False |
| locations[6].source.display_name | Zenodo (CERN European Organization for Nuclear Research) |
| locations[6].source.host_organization | https://openalex.org/I67311998 |
| locations[6].source.host_organization_name | European Organization for Nuclear Research |
| locations[6].source.host_organization_lineage | https://openalex.org/I67311998 |
| locations[6].license | cc-by |
| locations[6].pdf_url | |
| locations[6].version | submittedVersion |
| locations[6].raw_type | info:eu-repo/semantics/article |
| locations[6].license_id | https://openalex.org/licenses/cc-by |
| locations[6].is_accepted | False |
| locations[6].is_published | False |
| locations[6].raw_source_name | Sensors, Volume 21(Issue 14), (2021-10-04) |
| locations[6].landing_page_url | https://zenodo.org/record/5547209 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5030132038 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-1926-4359 |
| authorships[0].author.display_name | Nils Mandischer |
| authorships[0].countries | DE |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I887968799 |
| authorships[0].affiliations[0].raw_affiliation_string | Machine Dynamics and Robotics (IGMR), Institute of Mechanism Theory, RWTH Aachen University, 52074 Aachen, Germany |
| authorships[0].institutions[0].id | https://openalex.org/I887968799 |
| authorships[0].institutions[0].ror | https://ror.org/04xfq0f34 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I887968799 |
| authorships[0].institutions[0].country_code | DE |
| authorships[0].institutions[0].display_name | RWTH Aachen University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Nils Mandischer |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Machine Dynamics and Robotics (IGMR), Institute of Mechanism Theory, RWTH Aachen University, 52074 Aachen, Germany |
| authorships[1].author.id | https://openalex.org/A5003647976 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Tobias Huhn |
| authorships[1].countries | DE |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I887968799 |
| authorships[1].affiliations[0].raw_affiliation_string | Machine Dynamics and Robotics (IGMR), Institute of Mechanism Theory, RWTH Aachen University, 52074 Aachen, Germany |
| authorships[1].institutions[0].id | https://openalex.org/I887968799 |
| authorships[1].institutions[0].ror | https://ror.org/04xfq0f34 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I887968799 |
| authorships[1].institutions[0].country_code | DE |
| authorships[1].institutions[0].display_name | RWTH Aachen University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Tobias Huhn |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Machine Dynamics and Robotics (IGMR), Institute of Mechanism Theory, RWTH Aachen University, 52074 Aachen, Germany |
| authorships[2].author.id | https://openalex.org/A5018793970 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-8949-0215 |
| authorships[2].author.display_name | Mathias Hüsing |
| authorships[2].countries | DE |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I887968799 |
| authorships[2].affiliations[0].raw_affiliation_string | Machine Dynamics and Robotics (IGMR), Institute of Mechanism Theory, RWTH Aachen University, 52074 Aachen, Germany |
| authorships[2].institutions[0].id | https://openalex.org/I887968799 |
| authorships[2].institutions[0].ror | https://ror.org/04xfq0f34 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I887968799 |
| authorships[2].institutions[0].country_code | DE |
| authorships[2].institutions[0].display_name | RWTH Aachen University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Mathias Hüsing |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Machine Dynamics and Robotics (IGMR), Institute of Mechanism Theory, RWTH Aachen University, 52074 Aachen, Germany |
| authorships[3].author.id | https://openalex.org/A5054447183 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-1824-3433 |
| authorships[3].author.display_name | Burkhard Corves |
| authorships[3].countries | DE |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I887968799 |
| authorships[3].affiliations[0].raw_affiliation_string | Machine Dynamics and Robotics (IGMR), Institute of Mechanism Theory, RWTH Aachen University, 52074 Aachen, Germany |
| authorships[3].institutions[0].id | https://openalex.org/I887968799 |
| authorships[3].institutions[0].ror | https://ror.org/04xfq0f34 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I887968799 |
| authorships[3].institutions[0].country_code | DE |
| authorships[3].institutions[0].display_name | RWTH Aachen University |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Burkhard Corves |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Machine Dynamics and Robotics (IGMR), Institute of Mechanism Theory, RWTH Aachen University, 52074 Aachen, Germany |
| 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/1424-8220/21/14/4818/pdf?version=1626317957 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Efficient and Consumer-Centered Item Detection and Classification with a Multicamera Network at High Ranges |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10191 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9983000159263611 |
| 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 | Robotics and Sensor-Based Localization |
| related_works | https://openalex.org/W3037187668, https://openalex.org/W4234772502, https://openalex.org/W2380685755, https://openalex.org/W2252100032, https://openalex.org/W2963436428, https://openalex.org/W4400978025, https://openalex.org/W2918743509, https://openalex.org/W4388446985, https://openalex.org/W3213722473, https://openalex.org/W2110944602 |
| cited_by_count | 4 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 2 |
| counts_by_year[2].year | 2022 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 7 |
| best_oa_location.id | doi:10.3390/s21144818 |
| 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/1424-8220/21/14/4818/pdf?version=1626317957 |
| 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/s21144818 |
| primary_location.id | doi:10.3390/s21144818 |
| 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/1424-8220/21/14/4818/pdf?version=1626317957 |
| 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/s21144818 |
| publication_date | 2021-07-14 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W3208677988, https://openalex.org/W6606007657, https://openalex.org/W1953914880, https://openalex.org/W2611724155, https://openalex.org/W2109200236, https://openalex.org/W6678135826, https://openalex.org/W2145023731, https://openalex.org/W1841961408, https://openalex.org/W2950642167, https://openalex.org/W2624503621, https://openalex.org/W6747904511, https://openalex.org/W2963509914, https://openalex.org/W1991544872, https://openalex.org/W4248936881, https://openalex.org/W1579871682, https://openalex.org/W2065429801, https://openalex.org/W2130293653, https://openalex.org/W2560609797, https://openalex.org/W2939221413, https://openalex.org/W4251902048, https://openalex.org/W2124386111, https://openalex.org/W2979750740, https://openalex.org/W2963121255, https://openalex.org/W149045207 |
| referenced_works_count | 24 |
| abstract_inverted_index.a | 25, 87, 131, 147 |
| abstract_inverted_index.40 | 135 |
| abstract_inverted_index.EU | 2 |
| abstract_inverted_index.In | 0, 37, 107 |
| abstract_inverted_index.an | 16 |
| abstract_inverted_index.at | 99, 152 |
| abstract_inverted_index.in | 15, 55, 71, 122 |
| abstract_inverted_index.is | 24, 60, 86, 128 |
| abstract_inverted_index.of | 20, 58, 63, 73, 89, 102, 134, 150 |
| abstract_inverted_index.on | 50, 130 |
| abstract_inverted_index.to | 13, 104, 119, 140 |
| abstract_inverted_index.up | 103, 139 |
| abstract_inverted_index.we | 40, 67, 110 |
| abstract_inverted_index.84% | 151 |
| abstract_inverted_index.Hz. | 154 |
| abstract_inverted_index.One | 19 |
| abstract_inverted_index.Our | 84 |
| abstract_inverted_index.The | 126 |
| abstract_inverted_index.and | 11, 35, 47, 95, 137, 144 |
| abstract_inverted_index.are | 6 |
| abstract_inverted_index.for | 27, 45, 82, 93 |
| abstract_inverted_index.sqm | 136 |
| abstract_inverted_index.the | 1, 21, 42, 51, 56, 61, 64, 112, 123 |
| abstract_inverted_index.0.85 | 153 |
| abstract_inverted_index.fast | 94 |
| abstract_inverted_index.from | 115 |
| abstract_inverted_index.full | 113 |
| abstract_inverted_index.high | 100 |
| abstract_inverted_index.item | 33, 97, 120 |
| abstract_inverted_index.mean | 148 |
| abstract_inverted_index.nine | 141 |
| abstract_inverted_index.over | 117 |
| abstract_inverted_index.shop | 52, 132 |
| abstract_inverted_index.task | 28 |
| abstract_inverted_index.that | 8 |
| abstract_inverted_index.this | 38, 108 |
| abstract_inverted_index.used | 44 |
| abstract_inverted_index.with | 31, 77, 138 |
| abstract_inverted_index.Thus, | 66 |
| abstract_inverted_index.allow | 9 |
| abstract_inverted_index.eight | 105 |
| abstract_inverted_index.favor | 72 |
| abstract_inverted_index.floor | 133 |
| abstract_inverted_index.items | 49, 143 |
| abstract_inverted_index.major | 22 |
| abstract_inverted_index.work, | 39, 109 |
| abstract_inverted_index.floor. | 53 |
| abstract_inverted_index.humans | 10 |
| abstract_inverted_index.ranges | 101 |
| abstract_inverted_index.robots | 12 |
| abstract_inverted_index.context | 57 |
| abstract_inverted_index.coupled | 30, 76 |
| abstract_inverted_index.lenient | 78 |
| abstract_inverted_index.machine | 79 |
| abstract_inverted_index.meters. | 106 |
| abstract_inverted_index.methods | 5, 43, 70, 81, 91 |
| abstract_inverted_index.present | 41, 111 |
| abstract_inverted_index.project | 3 |
| abstract_inverted_index.accuracy | 149 |
| abstract_inverted_index.adjusted | 92 |
| abstract_inverted_index.context. | 125 |
| abstract_inverted_index.learning | 80 |
| abstract_inverted_index.pipeline | 114, 127 |
| abstract_inverted_index.planning | 29 |
| abstract_inverted_index.reaching | 146 |
| abstract_inverted_index.reliable | 96 |
| abstract_inverted_index.renounce | 68 |
| abstract_inverted_index.Important | 54 |
| abstract_inverted_index.SHAREWORK | 59 |
| abstract_inverted_index.algorithm | 85 |
| abstract_inverted_index.automated | 32 |
| abstract_inverted_index.detecting | 46 |
| abstract_inverted_index.detection | 34, 98 |
| abstract_inverted_index.developed | 7 |
| abstract_inverted_index.different | 142 |
| abstract_inverted_index.framework | 26 |
| abstract_inverted_index.validated | 129 |
| abstract_inverted_index.SHAREWORK, | 4 |
| abstract_inverted_index.industrial | 17, 124 |
| abstract_inverted_index.assemblies, | 145 |
| abstract_inverted_index.classifying | 48 |
| abstract_inverted_index.collaborate | 14 |
| abstract_inverted_index.combination | 88 |
| abstract_inverted_index.established | 90 |
| abstract_inverted_index.calibration, | 116 |
| abstract_inverted_index.environment. | 18 |
| abstract_inverted_index.methodology. | 65 |
| abstract_inverted_index.segmentation | 75, 118 |
| abstract_inverted_index.unsupervised | 74 |
| abstract_inverted_index.contributions | 23 |
| abstract_inverted_index.localization. | 36 |
| abstract_inverted_index.classification | 121 |
| abstract_inverted_index.classification. | 83 |
| abstract_inverted_index.user-friendliness | 62 |
| abstract_inverted_index.heavy-learning-based | 69 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5030132038 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I887968799 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.5699999928474426 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.82443478 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |