SUPER RESOLUTION MASK RCNN BASED TRANSFER DEEP LEARNING APPROACH FOR IDENTIFICATION OF BIRD SPECIES Article Swipe
Spotting the difference between bird species is a challenging task because the minute characteristics cannot be distinguished by the human eye. This identification problem is an example of fine grained classification task. The algorithm in such cases should be strong enough to identify small differences .However; there can be multiple problems such as orientation of bird, background colours, brightness and intensity of image which makes it difficult to correctly classify an image. The proposed paper presents a novel approach towards identification of species by increasing the resolution of image and applying Mask RCNN and custom net for classification. SRCNN with Mask RCNN and Inception V3 achieves 51.73% precison , 49.68% recall and 53.52 F1 Scor
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3803212
- OA Status
- green
- Cited By
- 4
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3154854122
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3154854122Canonical identifier for this work in OpenAlex
- Title
-
SUPER RESOLUTION MASK RCNN BASED TRANSFER DEEP LEARNING APPROACH FOR IDENTIFICATION OF BIRD SPECIESWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-03-12Full publication date if available
- Authors
-
Sofia Pillai, M. M. Raghuwanshi, Prerna BorkarList of authors in order
- Landing page
-
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3803212Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3803212Direct OA link when available
- Concepts
-
Artificial intelligence, Identification (biology), Computer science, Spotting, Task (project management), Transfer of learning, Recall, Pattern recognition (psychology), Orientation (vector space), Image (mathematics), Computer vision, Machine learning, Biology, Mathematics, Engineering, Psychology, Ecology, Cognitive psychology, Geometry, Systems engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2, 2023: 2Per-year citation counts (last 5 years)
- Related works (count)
-
20Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3154854122 |
|---|---|
| doi | |
| ids.mag | 3154854122 |
| ids.openalex | https://openalex.org/W3154854122 |
| fwci | 0.39012971 |
| type | article |
| title | SUPER RESOLUTION MASK RCNN BASED TRANSFER DEEP LEARNING APPROACH FOR IDENTIFICATION OF BIRD SPECIES |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T12388 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 0.9868999719619751 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1312 |
| topics[0].subfield.display_name | Molecular Biology |
| topics[0].display_name | Identification and Quantification in Food |
| topics[1].id | https://openalex.org/T11665 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9039000272750854 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1309 |
| topics[1].subfield.display_name | Developmental Biology |
| topics[1].display_name | Animal Vocal Communication and Behavior |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C154945302 |
| concepts[0].level | 1 |
| concepts[0].score | 0.7340350151062012 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[0].display_name | Artificial intelligence |
| concepts[1].id | https://openalex.org/C116834253 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6449017524719238 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q2039217 |
| concepts[1].display_name | Identification (biology) |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.6116458773612976 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C2779506182 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5882669687271118 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q7580141 |
| concepts[3].display_name | Spotting |
| concepts[4].id | https://openalex.org/C2780451532 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5583711862564087 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q759676 |
| concepts[4].display_name | Task (project management) |
| concepts[5].id | https://openalex.org/C150899416 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5440572500228882 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q1820378 |
| concepts[5].display_name | Transfer of learning |
| concepts[6].id | https://openalex.org/C100660578 |
| concepts[6].level | 2 |
| concepts[6].score | 0.5177220702171326 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q18733 |
| concepts[6].display_name | Recall |
| concepts[7].id | https://openalex.org/C153180895 |
| concepts[7].level | 2 |
| concepts[7].score | 0.5151451826095581 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[7].display_name | Pattern recognition (psychology) |
| concepts[8].id | https://openalex.org/C16345878 |
| concepts[8].level | 2 |
| concepts[8].score | 0.46074262261390686 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q107472979 |
| concepts[8].display_name | Orientation (vector space) |
| concepts[9].id | https://openalex.org/C115961682 |
| concepts[9].level | 2 |
| concepts[9].score | 0.4521508514881134 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[9].display_name | Image (mathematics) |
| concepts[10].id | https://openalex.org/C31972630 |
| concepts[10].level | 1 |
| concepts[10].score | 0.34351247549057007 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[10].display_name | Computer vision |
| concepts[11].id | https://openalex.org/C119857082 |
| concepts[11].level | 1 |
| concepts[11].score | 0.32136180996894836 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[11].display_name | Machine learning |
| concepts[12].id | https://openalex.org/C86803240 |
| concepts[12].level | 0 |
| concepts[12].score | 0.1412903070449829 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[12].display_name | Biology |
| concepts[13].id | https://openalex.org/C33923547 |
| concepts[13].level | 0 |
| concepts[13].score | 0.1351989507675171 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[13].display_name | Mathematics |
| concepts[14].id | https://openalex.org/C127413603 |
| concepts[14].level | 0 |
| concepts[14].score | 0.10270354151725769 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[14].display_name | Engineering |
| concepts[15].id | https://openalex.org/C15744967 |
| concepts[15].level | 0 |
| concepts[15].score | 0.08900579810142517 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[15].display_name | Psychology |
| concepts[16].id | https://openalex.org/C18903297 |
| concepts[16].level | 1 |
| concepts[16].score | 0.07524144649505615 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q7150 |
| concepts[16].display_name | Ecology |
| concepts[17].id | https://openalex.org/C180747234 |
| concepts[17].level | 1 |
| concepts[17].score | 0.05739164352416992 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q23373 |
| concepts[17].display_name | Cognitive psychology |
| concepts[18].id | https://openalex.org/C2524010 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[18].display_name | Geometry |
| concepts[19].id | https://openalex.org/C201995342 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q682496 |
| concepts[19].display_name | Systems engineering |
| keywords[0].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[0].score | 0.7340350151062012 |
| keywords[0].display_name | Artificial intelligence |
| keywords[1].id | https://openalex.org/keywords/identification |
| keywords[1].score | 0.6449017524719238 |
| keywords[1].display_name | Identification (biology) |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.6116458773612976 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/spotting |
| keywords[3].score | 0.5882669687271118 |
| keywords[3].display_name | Spotting |
| keywords[4].id | https://openalex.org/keywords/task |
| keywords[4].score | 0.5583711862564087 |
| keywords[4].display_name | Task (project management) |
| keywords[5].id | https://openalex.org/keywords/transfer-of-learning |
| keywords[5].score | 0.5440572500228882 |
| keywords[5].display_name | Transfer of learning |
| keywords[6].id | https://openalex.org/keywords/recall |
| keywords[6].score | 0.5177220702171326 |
| keywords[6].display_name | Recall |
| keywords[7].id | https://openalex.org/keywords/pattern-recognition |
| keywords[7].score | 0.5151451826095581 |
| keywords[7].display_name | Pattern recognition (psychology) |
| keywords[8].id | https://openalex.org/keywords/orientation |
| keywords[8].score | 0.46074262261390686 |
| keywords[8].display_name | Orientation (vector space) |
| keywords[9].id | https://openalex.org/keywords/image |
| keywords[9].score | 0.4521508514881134 |
| keywords[9].display_name | Image (mathematics) |
| keywords[10].id | https://openalex.org/keywords/computer-vision |
| keywords[10].score | 0.34351247549057007 |
| keywords[10].display_name | Computer vision |
| keywords[11].id | https://openalex.org/keywords/machine-learning |
| keywords[11].score | 0.32136180996894836 |
| keywords[11].display_name | Machine learning |
| keywords[12].id | https://openalex.org/keywords/biology |
| keywords[12].score | 0.1412903070449829 |
| keywords[12].display_name | Biology |
| keywords[13].id | https://openalex.org/keywords/mathematics |
| keywords[13].score | 0.1351989507675171 |
| keywords[13].display_name | Mathematics |
| keywords[14].id | https://openalex.org/keywords/engineering |
| keywords[14].score | 0.10270354151725769 |
| keywords[14].display_name | Engineering |
| keywords[15].id | https://openalex.org/keywords/psychology |
| keywords[15].score | 0.08900579810142517 |
| keywords[15].display_name | Psychology |
| keywords[16].id | https://openalex.org/keywords/ecology |
| keywords[16].score | 0.07524144649505615 |
| keywords[16].display_name | Ecology |
| keywords[17].id | https://openalex.org/keywords/cognitive-psychology |
| keywords[17].score | 0.05739164352416992 |
| keywords[17].display_name | Cognitive psychology |
| language | en |
| locations[0].id | mag:3154854122 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210172589 |
| locations[0].source.issn | 1556-5068 |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1556-5068 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | SSRN Electronic Journal |
| locations[0].source.host_organization | https://openalex.org/I1318003438 |
| locations[0].source.host_organization_name | RELX Group (Netherlands) |
| locations[0].source.host_organization_lineage | https://openalex.org/I1318003438 |
| locations[0].license | |
| locations[0].pdf_url | |
| locations[0].version | submittedVersion |
| locations[0].raw_type | |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | SSRN Electronic Journal |
| locations[0].landing_page_url | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3803212 |
| authorships[0].author.id | https://openalex.org/A5042454304 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-9601-4922 |
| authorships[0].author.display_name | Sofia Pillai |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210146358 |
| authorships[0].affiliations[0].raw_affiliation_string | Research Scholar, G.H.Raisoni College of Engineering, Nagpur, India. |
| authorships[0].institutions[0].id | https://openalex.org/I4210146358 |
| authorships[0].institutions[0].ror | https://ror.org/03dp11s58 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210146358 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | Raisoni Group of Institutions |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Sofia K. Pillai |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Research Scholar, G.H.Raisoni College of Engineering, Nagpur, India. |
| authorships[1].author.id | https://openalex.org/A5091230568 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-9545-4467 |
| authorships[1].author.display_name | M. M. Raghuwanshi |
| authorships[1].affiliations[0].raw_affiliation_string | Professor, Department of Information Technology, GHRCEM, Pune, India. |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | M. M. Raghuwanshi |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Professor, Department of Information Technology, GHRCEM, Pune, India. |
| authorships[2].author.id | https://openalex.org/A5000500170 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Prerna Borkar |
| authorships[2].countries | IN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I167153416 |
| authorships[2].affiliations[0].raw_affiliation_string | Mechanical Engineering Department, Priyadarshini College of Engineering, Nagpur 440019, India |
| authorships[2].institutions[0].id | https://openalex.org/I167153416 |
| authorships[2].institutions[0].ror | https://ror.org/02zrtpp84 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I167153416 |
| authorships[2].institutions[0].country_code | IN |
| authorships[2].institutions[0].display_name | Visvesvaraya National Institute of Technology |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Prerna Borkar |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Mechanical Engineering Department, Priyadarshini College of Engineering, Nagpur 440019, India |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3803212 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | SUPER RESOLUTION MASK RCNN BASED TRANSFER DEEP LEARNING APPROACH FOR IDENTIFICATION OF BIRD SPECIES |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-10-10T17:16:08.811792 |
| primary_topic.id | https://openalex.org/T12388 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 0.9868999719619751 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1312 |
| primary_topic.subfield.display_name | Molecular Biology |
| primary_topic.display_name | Identification and Quantification in Food |
| related_works | https://openalex.org/W3176974407, https://openalex.org/W2049750909, https://openalex.org/W2617900436, https://openalex.org/W1995026832, https://openalex.org/W2583510596, https://openalex.org/W3107840264, https://openalex.org/W3096507551, https://openalex.org/W2205137396, https://openalex.org/W2948691720, https://openalex.org/W3003014844, https://openalex.org/W1981824936, https://openalex.org/W3027435983, https://openalex.org/W1998248682, https://openalex.org/W1657294672, https://openalex.org/W3196890180, https://openalex.org/W1553261160, https://openalex.org/W3021775880, https://openalex.org/W1964238623, https://openalex.org/W2966235325, https://openalex.org/W3162804781 |
| cited_by_count | 4 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 2 |
| locations_count | 1 |
| best_oa_location.id | mag:3154854122 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210172589 |
| best_oa_location.source.issn | 1556-5068 |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1556-5068 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | SSRN Electronic Journal |
| best_oa_location.source.host_organization | https://openalex.org/I1318003438 |
| best_oa_location.source.host_organization_name | RELX Group (Netherlands) |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I1318003438 |
| best_oa_location.license | |
| best_oa_location.pdf_url | |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | SSRN Electronic Journal |
| best_oa_location.landing_page_url | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3803212 |
| primary_location.id | mag:3154854122 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210172589 |
| primary_location.source.issn | 1556-5068 |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1556-5068 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | SSRN Electronic Journal |
| primary_location.source.host_organization | https://openalex.org/I1318003438 |
| primary_location.source.host_organization_name | RELX Group (Netherlands) |
| primary_location.source.host_organization_lineage | https://openalex.org/I1318003438 |
| primary_location.license | |
| primary_location.pdf_url | |
| primary_location.version | submittedVersion |
| primary_location.raw_type | |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | SSRN Electronic Journal |
| primary_location.landing_page_url | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3803212 |
| publication_date | 2021-03-12 |
| publication_year | 2021 |
| referenced_works_count | 0 |
| abstract_inverted_index., | 108 |
| abstract_inverted_index.a | 7, 76 |
| abstract_inverted_index.F1 | 113 |
| abstract_inverted_index.V3 | 104 |
| abstract_inverted_index.an | 25, 70 |
| abstract_inverted_index.as | 52 |
| abstract_inverted_index.be | 15, 38, 48 |
| abstract_inverted_index.by | 17, 83 |
| abstract_inverted_index.in | 34 |
| abstract_inverted_index.is | 6, 24 |
| abstract_inverted_index.it | 65 |
| abstract_inverted_index.of | 27, 54, 61, 81, 87 |
| abstract_inverted_index.to | 41, 67 |
| abstract_inverted_index.The | 32, 72 |
| abstract_inverted_index.and | 59, 89, 93, 102, 111 |
| abstract_inverted_index.can | 47 |
| abstract_inverted_index.for | 96 |
| abstract_inverted_index.net | 95 |
| abstract_inverted_index.the | 1, 11, 18, 85 |
| abstract_inverted_index.Mask | 91, 100 |
| abstract_inverted_index.RCNN | 92, 101 |
| abstract_inverted_index.Scor | 114 |
| abstract_inverted_index.This | 21 |
| abstract_inverted_index.bird | 4 |
| abstract_inverted_index.eye. | 20 |
| abstract_inverted_index.fine | 28 |
| abstract_inverted_index.such | 35, 51 |
| abstract_inverted_index.task | 9 |
| abstract_inverted_index.with | 99 |
| abstract_inverted_index.53.52 | 112 |
| abstract_inverted_index.SRCNN | 98 |
| abstract_inverted_index.bird, | 55 |
| abstract_inverted_index.cases | 36 |
| abstract_inverted_index.human | 19 |
| abstract_inverted_index.image | 62, 88 |
| abstract_inverted_index.makes | 64 |
| abstract_inverted_index.novel | 77 |
| abstract_inverted_index.paper | 74 |
| abstract_inverted_index.small | 43 |
| abstract_inverted_index.task. | 31 |
| abstract_inverted_index.there | 46 |
| abstract_inverted_index.which | 63 |
| abstract_inverted_index.49.68% | 109 |
| abstract_inverted_index.51.73% | 106 |
| abstract_inverted_index.cannot | 14 |
| abstract_inverted_index.custom | 94 |
| abstract_inverted_index.enough | 40 |
| abstract_inverted_index.image. | 71 |
| abstract_inverted_index.minute | 12 |
| abstract_inverted_index.recall | 110 |
| abstract_inverted_index.should | 37 |
| abstract_inverted_index.strong | 39 |
| abstract_inverted_index.because | 10 |
| abstract_inverted_index.between | 3 |
| abstract_inverted_index.example | 26 |
| abstract_inverted_index.grained | 29 |
| abstract_inverted_index.problem | 23 |
| abstract_inverted_index.species | 5, 82 |
| abstract_inverted_index.towards | 79 |
| abstract_inverted_index.Spotting | 0 |
| abstract_inverted_index.achieves | 105 |
| abstract_inverted_index.applying | 90 |
| abstract_inverted_index.approach | 78 |
| abstract_inverted_index.classify | 69 |
| abstract_inverted_index.colours, | 57 |
| abstract_inverted_index.identify | 42 |
| abstract_inverted_index.multiple | 49 |
| abstract_inverted_index.precison | 107 |
| abstract_inverted_index.presents | 75 |
| abstract_inverted_index.problems | 50 |
| abstract_inverted_index.proposed | 73 |
| abstract_inverted_index..However; | 45 |
| abstract_inverted_index.Inception | 103 |
| abstract_inverted_index.algorithm | 33 |
| abstract_inverted_index.correctly | 68 |
| abstract_inverted_index.difficult | 66 |
| abstract_inverted_index.intensity | 60 |
| abstract_inverted_index.background | 56 |
| abstract_inverted_index.brightness | 58 |
| abstract_inverted_index.difference | 2 |
| abstract_inverted_index.increasing | 84 |
| abstract_inverted_index.resolution | 86 |
| abstract_inverted_index.challenging | 8 |
| abstract_inverted_index.differences | 44 |
| abstract_inverted_index.orientation | 53 |
| abstract_inverted_index.distinguished | 16 |
| abstract_inverted_index.classification | 30 |
| abstract_inverted_index.identification | 22, 80 |
| abstract_inverted_index.characteristics | 13 |
| abstract_inverted_index.classification. | 97 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 94 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.7099999785423279 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.5694068 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |