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ImageNet-1k is a dataset often used for benchmarking machine learning (ML) models and evaluating tasks such as image recognition and object detection.
WordNet: a lexical database for English
George A Miller · 1995
Earlier work this paper cites.
ImageNet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
eBird: A citizen-based bird observation network in the biological sciences
Brian L Sullivan, Christopher L Wood, Marshall J Iliff, Rick E Bonney, Daniel Fink, and Steve Kelling · 2009
Earlier work this paper cites.
How many species are there on Earth and in the ocean?
Camilo Mora, Derek P Tittensor, Sina Adl, Alastair GB Simpson, and Boris Worm · 2011
Earlier work this paper cites.
Microsoft COCO: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
ImageNet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Earlier work this paper cites.
Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection
Grant Van Horn, Steve Branson, Ryan Farrell, Scott Haber, Jessie Barry, Panos Ipeirotis, Pietro Perona, and Serge Belongie · 2015
Earlier work this paper cites.
Stories we tell about labor: Turkopticon and the trouble with" design"
Lilly C Irani and M Six Silberman · 2016
Earlier work this paper cites.
The devil is in the tails: Fine-grained classification in the wild
Grant Van Horn and Pietro Perona · 2017
Earlier work this paper cites.
Recognition in terra incognita
Sara Beery, Grant Van Horn, and Pietro Perona · 2018
Cited alongside, same era.
The iNaturalist species classification and detection dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie · 2018
Cited alongside, same era.
Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
Andrei Barbu, David Mayo, Julian Alverio, William Luo, Christopher Wang, Dan Gutfreund, Josh Tenenbaum, and Boris Katz · 2019
Cited alongside, same era.
The iWildcam 2018 challenge dataset
Sara Beery, Grant Van Horn, Oisin Mac Aodha, and Pietro Perona · 2019
Cited alongside, same era.
Excavating AI: The politics of images in machine learning training sets
Kate Crawford and Trevor Paglen · 2019
Cited alongside, same era.
From ImageNet to image classification: Contextualizing progress on benchmarks
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, and Aleksander Madry · 2020
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Towards fairer datasets: Filtering and balancing the distribution of the people subtree in the ImageNet hierarchy
Kaiyu Yang, Klint Qinami, Li Fei-Fei, Jia Deng, and Olga Russakovsky · 2020
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The iWildCam 2021 competition dataset
Sara Beery, Arushi Agarwal, Elijah Cole, and Vighnesh Birodkar · 2021
Later among the works it cites.
Reduced, reused and recycled: The life of a dataset in machine learning research
Bernard Koch, Emily Denton, Alex Hanna, and Jacob G Foster · 2021
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Pervasive label errors in test sets destabilize machine learning benchmarks
Curtis G Northcutt, Anish Athalye, and Jonas Mueller · 2021
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Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, and Vaishaal Shankar · 2019
Cited alongside, same era.
Do we train on test data? purging CIFAR of near-duplicates
Björn Barz and Joachim Denzler · 2020
Cited alongside, same era.
Lucas Beyer, Olivier J Hénaff, Alexander Kolesnikov, Xiaohua Zhai, and Aäron van den Oord · 2020
Cited alongside, same era.
Bringing the people back in: Contesting benchmark machine learning datasets
Emily Denton, Alex Hanna, Razvan Amironesei, Andrew Smart, Hilary Nicole, and Morgan Klaus Scheuerman · 2020
Cited alongside, same era.
Large image datasets: A pyrrhic win for computer vision?
Vinay Uday Prabhu and Abeba Birhane · 2021
Later among the works it cites.
Do datasets have politics? disciplinary values in computer vision dataset development
Morgan Klaus Scheuerman, Alex Hanna, and Emily Denton · 2021
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Beyond fair pay: Ethical implications of nlp crowdsourcing
Boaz Shmueli, Jan Fell, Soumya Ray, and Lun-Wei Ku · 2021
Later among the works it cites.
A study of face obfuscation in ImageNet
Kaiyu Yang, Jacqueline Yau, Li Fei-Fei, Jia Deng, and Olga Russakovsky · 2022
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