| Creating xBD: A Dataset for Assessing Building Damage from Satellite Imagery R Gupta, B Goodman, N Patel, R Hosfelt, S Sajeev, E Heim, J Doshi, ... The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 367 | 2019 |
| Cough Against COVID: Evidence of COVID-19 Signature in Cough Sounds P Bagad*, A Dalmia*, J Doshi*, A Nagrani, P Bhamare, A Mahale, S Rane, ... arXiv preprint arXiv:2009.08790, 2020 | 131 | 2020 |
| From Satellite Imagery to Disaster Insights J Doshi, S Basu, G Pang AI for Social Good Workshop, Neural Information Processing Systems (NeurIPS), 2018 | 84 | 2018 |
| Residual Inception Skip Network for Binary Segmentation J Doshi The IEEE Conference on Computer Vision and Pattern Recognition (CVPRW) Workshop, 2018 | 39 | 2018 |
| From deep learning to episodic memories: Creating categories of visual experiences J Doshi, Z Kira, A Wagner Proceedings of the third annual conference on advances in cognitive systems …, 2015 | 22 | 2015 |
| xbd: A dataset for assessing building damage from satellite imagery R Gupta, R Hosfelt, S Sajeev, N Patel, B Goodman, J Doshi, E Heim, ... arXiv preprint arXiv:1911.09296, 2019 | 19 | 2019 |
| FireNet: Real-time Segmentation of Fire Perimeter from Aerial Video J Doshi, D Garcia, C Massey, P Llueca, N Borensztein, M Baird, M Cook, ... Humanitarian Assistance and Disaster Response workshop, Neurips 2019, 2019 | 16 | 2019 |
| Gaston, M. xbd: A dataset for assessing building damage from satellite imagery. arXiv R Gupta, R Hosfelt, S Sajeev, N Patel, B Goodman, J Doshi, E Heim, ... arXiv preprint arXiv:1911.09296, 2019 | 14 | 2019 |
| Multi-class segmentation under severe class imbalance: A case study in roof damage assessment JB Boin, N Roth, J Doshi, P Llueca, N Borensztein Humanitarian Assistance and Disaster Response workshop, Neurips 2020, 2020 | 10 | 2020 |
| Cough against COVID: evidence of COVID-19 signature in cough sounds. arXiv.(2020). doi: 10.48550 P Bagad, A Dalmia, J Doshi, A Nagrani, P Bhamare, A Mahale arXiv, 2009 | 7 | 2009 |
| Impact of data-splits on generalization: Identifying COVID-19 from cough and context M Sharma*, N Shenoy*, J Doshi*, P Bagad, A Dalmia, P Bhamare, ... AI for Public Health Workshop, ICLR 2021, 2021 | 5 | 2021 |
| Who, how, where: Using exemplars to learn social concepts AR Wagner, J Doshi Social Robotics: 5th International Conference, ICSR 2013, Bristol, UK …, 2013 | 4 | 2013 |
| A Case for Rejection in Low Resource ML Deployment J White, P Madaan, N Shenoy, A Agnihotri, M Sharma, J Doshi Deployment and Monitoring ML Systems workshop, Neurips 2022, 2022 | 2 | 2022 |
| BOLLWM: A real-world dataset for bollworm pest monitoring from cotton fields in India J White, C Agrawal, A Ojha, A Agnihotri, M Sharma, J Doshi arXiv preprint arXiv:2304.00763, 2023 | 1 | 2023 |
| The LLM Landscape for LMICs: Overview, Evaluation Framework, Evaluation Components, Initial Recommendations J Doshi, K Jois, A Kumar, K Hanna, P Anandan https://drive.google.com/file/d/11q2PJgRkFvCV1u-5XX0CHzjiuusn5rIi/view, 2023 | | 2023 |
| Using Machine Learning to Identify and Classify Planetary Landing Site Dangers and Roving Vehicle Obstacles in Remotely Sensed Satellite Imagery and Drone Videos L Schurmeier, J Doshi, P Garcia AGU Fall Meeting Abstracts 2019, P43E-3517, 2019 | | 2019 |
| Spatio-Temporal Deep Features for Surveillance Event Detection J Doshi, Y Cheng, L Brown, Q Fan, R Feris, S Pankanti 10th Machine Learning Symposium, 2016 | | 2016 |
| Deep Segments: Comparisons between Scenes and their Constituent Fragments using Deep Learning J Doshi, C Mason, A Wagner, Z Kira Georgia Institute of Technology, 2014 | | 2014 |
Ritwik GuptaUniversity of California, BerkeleyVerified email at berkeley.edu
