Imagenet large scale visual recognition challenge O Russakovsky, J Deng, H Su, J Krause, S Satheesh, S Ma, Z Huang, ... International journal of computer vision 115, 211-252, 2015 | 46936 | 2015 |
3d object representations for fine-grained categorization J Krause, M Stark, J Deng, L Fei-Fei Proceedings of the IEEE international conference on computer vision …, 2013 | 4108 | 2013 |
Fine-grained recognition without part annotations J Krause, H Jin, J Yang, L Fei-Fei Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 585 | 2015 |
Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States T Gebru, J Krause, Y Wang, D Chen, J Deng, EL Aiden, L Fei-Fei Proceedings of the National Academy of Sciences 114 (50), 13108-13113, 2017 | 569 | 2017 |
Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy J Krause, V Gulshan, E Rahimy, P Karth, K Widner, GS Corrado, L Peng, ... Ophthalmology 125 (8), 1264-1272, 2018 | 520 | 2018 |
A hierarchical approach for generating descriptive image paragraphs J Krause, J Johnson, R Krishna, L Fei-Fei Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 452 | 2017 |
How to read articles that use machine learning: users’ guides to the medical literature Y Liu, PHC Chen, J Krause, L Peng Jama 322 (18), 1806-1816, 2019 | 439 | 2019 |
The unreasonable effectiveness of noisy data for fine-grained recognition J Krause, B Sapp, A Howard, H Zhou, A Toshev, T Duerig, J Philbin, ... Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 434 | 2016 |
Using a deep learning algorithm and integrated gradients explanation to assist grading for diabetic retinopathy R Sayres, A Taly, E Rahimy, K Blumer, D Coz, N Hammel, J Krause, ... Ophthalmology 126 (4), 552-564, 2019 | 404 | 2019 |
Fine-grained crowdsourcing for fine-grained recognition J Deng, J Krause, L Fei-Fei Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 389 | 2013 |
Tool detection and operative skill assessment in surgical videos using region-based convolutional neural networks A Jin, S Yeung, J Jopling, J Krause, D Azagury, A Milstein, L Fei-Fei 2018 IEEE winter conference on applications of computer vision (WACV), 691-699, 2018 | 327 | 2018 |
Hedging Your Bets: Optimizing Accuracy-Specificity Trade-offs in Large Scale Visual Recognition J Deng, J Krause, AC Berg, L Fei-Fei | 251 | 2012 |
Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program P Ruamviboonsuk, J Krause, P Chotcomwongse, R Sayres, R Raman, ... NPJ digital medicine 2 (1), 25, 2019 | 224* | 2019 |
The next big one: Detecting earthquakes and other rare events from community-based sensors M Faulkner, M Olson, R Chandy, J Krause, KM Chandy, A Krause Proceedings of the 10th ACM/IEEE International Conference on Information …, 2011 | 217 | 2011 |
Scalable multi-label annotation J Deng, O Russakovsky, J Krause, MS Bernstein, A Berg, L Fei-Fei Proceedings of the SIGCHI Conference on Human Factors in Computing Systems …, 2014 | 211 | 2014 |
Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs S Phene, RC Dunn, N Hammel, Y Liu, J Krause, N Kitade, ... Ophthalmology 126 (12), 1627-1639, 2019 | 174 | 2019 |
Learning features and parts for fine-grained recognition J Krause, T Gebru, J Deng, LJ Li, L Fei-Fei 2014 22nd International conference on pattern recognition, 26-33, 2014 | 153 | 2014 |
Collecting a large-scale dataset of fine-grained cars J Krause, J Deng, M Stark, L Fei-Fei | 127 | 2013 |
Fine-grained car detection for visual census estimation T Gebru, J Krause, Y Wang, D Chen, J Deng, L Fei-Fei Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 120 | 2017 |
Fine-Grained Categorization for 3D Scene Understanding M Stark, J Krause, B Pepik, D Meger, JJ Little, B Schiele, D Koller British Machine Vision Conference (BMVC), 2012 | 97 | 2012 |