About: Ross Girshick

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An Entity of Type : wikibase:Item, within Data Space : wikidata.demo.openlinksw.com associated with source document(s)

American computer scientist and machine learning researcher

Attributes	Values
rdf:type	Item
description	American computer scientist and machine learning researcher (en)
rdfs:label	Ross Brook Girshick (ga) Ross Brook Girshick (nl) Ross Girshick (en)
skos:prefLabel	Ross Brook Girshick (ga) Ross Brook Girshick (nl) Ross Girshick (en)
name	Ross Brook Girshick (ga) Ross Brook Girshick (nl) Ross Girshick (en)
ACM Digital Library author ID	wds:Q102406162-c60c252a-40a2-aa9f-1795-100d716638b4
ACM Digital Library author ID	81467645792
given name	wds:Q102406162-A78F1626-B2C2-4053-AE0B-3E78EEF711D0 wds:Q102406162-dba4010b-4ce3-2b81-9c13-590543c2f6ed
given name	Ross Brook
instance of	wds:Q102406162-417DB2CF-37DF-4D41-991B-EC353F5D788F
part of	wds:Q102406162-58ff6b33-4406-4264-9ac1-228181bd31d4
instance of	Homo sapiens
part of	Facebook AI Research
doctoral advisor	wds:Q102406162-61aec742-e98e-4c25-9dde-a8ec483e5221
MR Author ID	wds:Q102406162-9DED4D6E-237C-4EB6-99EC-4E35813AA586
Mathematics Genealogy Project ID	wds:Q102406162-02FF0C0E-99A7-4555-AE58-B8E2427D42AF
doctoral advisor	Pedro Felipe Felzenszwalb
MR Author ID	1101891
Mathematics Genealogy Project ID	171479
ResearchGate profile ID	wds:Q102406162-a9bb2284-4dbd-ee77-0f85-8d3b49642dbb
ResearchGate profile ID	Ross-Girshick
Google Scholar author ID	wds:Q102406162-200944f3-454e-47b0-38c5-1c8f5e574240
Google Scholar author ID	W8VIEZgAAAAJ
INSPIRE-HEP author ID	wds:Q102406162-31e7a560-4641-956d-c48e-72039a94b2bc
INSPIRE-HEP author ID	R.Girshick.1
skos:altLabel	Ross Brook Girshick (en)
occupation	wds:Q102406162-106af4b6-4dfa-2b81-7913-88ec982cea52
employer	wds:Q102406162-c84c7572-4204-0c64-9519-fae7bfac5171
GitHub username	wds:Q102406162-07a6403c-446a-6f78-60e0-2e4c711e948a
sex or gender	wds:Q102406162-187510e1-4f79-cca4-1434-0c1d1d7efbba
VIAF ID	wds:Q102406162-56dcf13b-45ed-828b-0bf7-118c1f04d75e
DBLP author ID	wds:Q102406162-ab0bb1db-468e-693f-63e5-5d72369ab745
IdRef ID	wds:Q102406162-39b08ee5-4376-615d-5b8d-395bc420387c
country of citizenship	wds:Q102406162-ccd25208-4e0c-c2a2-34de-4be778004b37
educated at	wds:Q102406162-f4adf91a-7974-44fb-bca2-d63507b0d882
family name	wds:Q102406162-30f4ff7f-46bf-b2fb-86b2-2e21f2e37ef1
official website	wds:Q102406162-534d9eb6-45c7-ef1f-b760-04dca97a55b0
VIAF ID	http://viaf.org/viaf/81158367617801281053
DBLP author ID	https://dblp.org/pid/89/7658.rdf
IdRef ID	http://www.idref.fr/242624103/id
occupation	computer scientist
employer	Meta Platforms
GitHub username	rbgirshick
sex or gender	male
VIAF ID	81158367617801281053
DBLP author ID	89/7658
IdRef ID	242624103
country of citizenship	United States of America
educated at	University of Chicago
family name	Girshick
official website	https://www.rossgirshick.info/
IEEE Xplore author ID	wds:Q102406162-172787cd-4f54-c8db-7e5f-af94b4fb2463
IEEE Xplore author ID	37546866400
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q102406162
is author of	Microsoft COCO: Common Objects in Context Caffe: Convolutional Architecture for Fast Feature Embedding Object detection with discriminatively trained part-based models Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. Efficient human pose estimation from single depth images. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation Focal Loss for Dense Object Detection Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation PHYRE: A New Benchmark for Physical Reasoning Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Mask R-CNN Fast R-CNN You Only Look Once: Unified, Real-Time Object Detection Generalized Sparselet Models for Real-Time Multiclass Object Recognition. Object Detection Networks on Convolutional Feature Maps. Impact of data on generalization of AI for surgical intelligence applications CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning Inferring and Executing Programs for Visual Reasoning Momentum Contrast for Unsupervised Visual Representation Learning LSDA: Large Scale Detection through Adaptation Object Detection with Grammar Models Object Instance Segmentation and Fine-Grained Localization Using Hypercolumns. Understanding Objects in Detail with Fine-Grained Attributes Feature Pyramid Networks for Object Detection Momentum Contrast for Unsupervised Visual Representation Learning
is author of	wds:Q37804409-2A5476D6-8D96-4EA8-A79E-46747B91586D wds:Q76470963-C449679B-02BE-435A-A6F9-2FB3511C3E7D wds:Q77622737-69ABE6B4-8182-4489-8095-1851D736BC4B wds:Q90441451-F2569390-332E-4BF1-B0BA-900DDF626066 wds:Q30337048-FCFF9E1C-6AC8-44BB-B37E-41E5FB21BED8 wds:Q50628729-21B4AAF1-D36B-462B-9ADF-4370DE8DFF7F wds:Q53357026-CB97B2AA-D716-4BF7-82A6-14FC7E4C5413 wds:Q63628666-4667DE4F-EC6E-4096-852A-00EB00211AEA wds:Q104495276-23153C69-1BCA-4AEC-9304-4158EB7ECAE6 wds:Q54379792-3978ECA9-2E59-4140-9741-7C4C6E710F4F wds:Q51150424-B5434DD6-5CFB-4939-8EDD-560597E203A0 wds:Q85683759-D5276D96-C4BD-4F51-8303-D63C3D797A62 wds:Q105794010-C86A68BF-1463-4E0B-8501-92C5819BB847

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