| Long-term recurrent convolutional networks for visual recognition and description J Donahue, L Anne Hendricks, S Guadarrama, M Rohrbach, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 6727 | 2015 |
| Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs V Gulshan, L Peng, M Coram, MC Stumpe, D Wu, A Narayanaswamy, ... Jama 316 (22), 2402-2410, 2016 | 5389 | 2016 |
| Sequence to sequence-video to text S Venugopalan, M Rohrbach, J Donahue, R Mooney, T Darrell, K Saenko Proceedings of the IEEE international conference on computer vision, 4534-4542, 2015 | 1523 | 2015 |
| Translating videos to natural language using deep recurrent neural networks S Venugopalan, H Xu, J Donahue, M Rohrbach, R Mooney, K Saenko Proceedings of the 2015 Conference of the North American Chapter of the …, 2014 | 1072 | 2014 |
| Detecting cancer metastases on gigapixel pathology images Y Liu, K Gadepalli, M Norouzi, GE Dahl, T Kohlberger, A Boyko, ... arXiv preprint arXiv:1703.02442, 2017 | 643 | 2017 |
| Youtube2text: Recognizing and describing arbitrary activities using semantic hierarchies and zero-shot recognition S Guadarrama, N Krishnamoorthy, G Malkarnenkar, S Venugopalan, ... Proceedings of the IEEE international conference on computer vision, 2712-2719, 2013 | 533 | 2013 |
| Deep compositional captioning: Describing novel object categories without paired training data LA Hendricks, S Venugopalan, M Rohrbach, R Mooney, K Saenko, ... Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 304 | 2016 |
| Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild. J Thomason, S Venugopalan, S Guadarrama, K Saenko, RJ Mooney International Conference on Computational Linguistics (COLING) 2 (5), 9, 2014 | 251 | 2014 |
| Captioning images with diverse objects S Venugopalan, LA Hendricks, M Rohrbach, R Mooney, T Darrell, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 190 | 2017 |
| Improving lstm-based video description with linguistic knowledge mined from text S Venugopalan, LA Hendricks, R Mooney, K Saenko Empirical Methods in Natural Language Processing (EMNLP-16), 1961--1966, 2016 | 152 | 2016 |
| Multimodal video description V Ramanishka, A Das, DH Park, S Venugopalan, LA Hendricks, ... Proceedings of the 24th ACM international conference on Multimedia, 1092-1096, 2016 | 134 | 2016 |
| Topic based classification and pattern identification in patents S Venugopalan, V Rai Technological Forecasting and Social Change 94, 236-250, 2015 | 123 | 2015 |
| Detection of anaemia from retinal fundus images via deep learning A Mitani, A Huang, S Venugopalan, GS Corrado, L Peng, DR Webster, ... Nature Biomedical Engineering 4 (1), 18-27, 2020 | 111 | 2020 |
| Predicting the risk of developing diabetic retinopathy using deep learning A Bora, S Balasubramanian, B Babenko, S Virmani, S Venugopalan, ... The Lancet Digital Health 3 (1), e10-e19, 2021 | 84 | 2021 |
| A multi-scale multiple instance video description network H Xu, S Venugopalan, V Ramanishka, M Rohrbach, K Saenko ICCV Workshop on Closing the Loop between Vision and Language, 2015 | 67 | 2015 |
| Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning AV Varadarajan, P Bavishi, P Ruamviboonsuk, P Chotcomwongse, ... Nature communications 11 (1), 130, 2020 | 65 | 2020 |
| Semantic text summarization of long videos S Sah, S Kulhare, A Gray, S Venugopalan, E Prud'Hommeaux, R Ptucha 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), 989-997, 2017 | 53 | 2017 |
| Attribution in scale and space S Xu, S Venugopalan, M Sundararajan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 39 | 2020 |
| Guided integrated gradients: An adaptive path method for removing noise A Kapishnikov, S Venugopalan, B Avci, B Wedin, M Terry, T Bolukbasi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 24 | 2021 |
| Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts L Schiff, B Migliori, Y Chen, D Carter, C Bonilla, J Hall, M Fan, E Tam, ... Nature Communications 13 (1), 1590, 2022 | 21* | 2022 |
Kate SaenkoBoston UniversityZweryfikowany adres z bu.edu
