| Wilds: A benchmark of in-the-wild distribution shifts PW Koh, S Sagawa, H Marklund, SM Xie, M Zhang, A Balsubramani, ... International conference on machine learning, 5637-5664, 2021 | 1532 | 2021 |
| Recognition in terra incognita S Beery, G Van Horn, P Perona Proceedings of the European conference on computer vision (ECCV), 456-473, 2018 | 1019 | 2018 |
| Perspectives in machine learning for wildlife conservation D Tuia, B Kellenberger, S Beery, BR Costelloe, S Zuffi, B Risse, A Mathis, ... Nature communications 13 (1), 1-15, 2022 | 493 | 2022 |
| Efficient pipeline for camera trap image review S Beery, D Morris, S Yang arXiv preprint arXiv:1907.06772, 2019 | 225* | 2019 |
| A deep active learning system for species identification and counting in camera trap images MS Norouzzadeh, D Morris, S Beery, N Joshi, N Jojic, J Clune Methods in ecology and evolution 12 (1), 150-161, 2021 | 210 | 2021 |
| The iwildcam 2021 competition dataset S Beery, A Agarwal, E Cole, V Birodkar arXiv preprint arXiv:2105.03494, 2021 | 203 | 2021 |
| Benchmarking representation learning for natural world image collections G Van Horn, E Cole, S Beery, K Wilber, S Belongie, O Mac Aodha Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 175 | 2021 |
| Context r-cnn: Long term temporal context for per-camera object detection S Beery, G Wu, V Rathod, R Votel, J Huang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 152 | 2020 |
| Extending the wilds benchmark for unsupervised adaptation S Sagawa, PW Koh, T Lee, I Gao, SM Xie, K Shen, A Kumar, W Hu, ... arXiv preprint arXiv:2112.05090, 2021 | 133 | 2021 |
| Synthetic examples improve generalization for rare classes S Beery, Y Liu, D Morris, J Piavis, A Kapoor, N Joshi, M Meister, P Perona Proceedings of the ieee/cvf winter conference on applications of computer …, 2020 | 120 | 2020 |
| Species distribution modeling for machine learning practitioners: A review S Beery, E Cole, J Parker, P Perona, K Winner Proceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable …, 2021 | 96 | 2021 |
| The auto arborist dataset: a large-scale benchmark for multiview urban forest monitoring under domain shift S Beery, G Wu, T Edwards, F Pavetic, B Majewski, S Mukherjee, S Chan, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 44 | 2022 |
| The iWildcam 2019 Challenge Dataset S Beery, D Morris, P Perona arXiv preprint arXiv:1907.07617, 4, 2019 | 42 | 2019 |
| The Caltech Fish Counting dataset: a benchmark for multiple-object tracking and counting J Kay, P Kulits, S Stathatos, S Deng, E Young, S Beery, G Van Horn, ... European Conference on Computer Vision, 290-311, 2022 | 32 | 2022 |
| Finding areas of motion in camera trap images A Miguel, S Beery, E Flores, L Klemesrud, R Bayrakcismith 2016 IEEE international conference on image processing (ICIP), 1334-1338, 2016 | 28 | 2016 |
| ElephantBook: A semi-automated human-in-the-loop system for elephant re-identification P Kulits, J Wall, A Bedetti, M Henley, S Beery Proceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable …, 2021 | 25 | 2021 |
| Mammalnet: A large-scale video benchmark for mammal recognition and behavior understanding J Chen, M Hu, DJ Coker, ML Berumen, B Costelloe, S Beery, A Rohrbach, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 19 | 2023 |
| Scaling biodiversity monitoring for the data age S Beery XRDS: Crossroads, The ACM Magazine for Students 27 (4), 14-18, 2021 | 12 | 2021 |
| Domain adaptation for rare classes augmented with synthetic samples T Das, RJ Bruintjes, A Lengyel, J van Gemert, S Beery arXiv preprint arXiv:2110.12216, 2021 | 9 | 2021 |
| Training machines to identify species using GBIF-mediated datasets T Robertson, S Belongie, A Hartwig, C Kaeser-Chen, C Zhang, KC Tan, ... Biodiversity Information Science and Standards, 2019 | 8 | 2019 |
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