Idrid: Diabetic retinopathy–segmentation and grading challenge P Porwal, S Pachade, M Kokare, G Deshmukh, J Son, W Bae, L Liu, ... Medical image analysis 59, 101561, 2020 | 259 | 2020 |
Crowdsourcing for chromosome segmentation and deep classification M Sharma*, O Saha*, A Sriraman, R Hebbalaguppe, L Vig, S Karande Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 106 | 2017 |
RNNPool: Efficient non-linear pooling for RAM constrained inference O Saha, A Kusupati, HV Simhadri, M Varma, P Jain Advances in Neural Information Processing Systems 33, 20473-20484, 2020 | 56 | 2020 |
EdgeML: Machine LEARNING for Resource-Constrained Edge Devices DK Dennis, Y Gaurkar, S Gopinath, S Goyal, C Gupta, M Jain, A Kumar, ... https://github. com/Microsoft/EdgeML, 2017 | 40 | 2017 |
Fully convolutional neural network for semantic segmentation of anatomical structure and pathologies in colour fundus images associated with diabetic retinopathy O Saha, R Sathish, D Sheet International Symposium of Biomedical Imaging, 2018 | 20 | 2018 |
GANORCON: Are generative models useful for few-shot segmentation? O Saha, Z Cheng, S Maji Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 17 | 2022 |
Learning with Multitask Adversaries using Weakly Labelled Data for Semantic Segmentation in Retinal Images O Saha, R Sathish, D Sheet International Conference on Medical Imaging with Deep Learning, 414-426, 2019 | 11 | 2019 |
Improving few-shot part segmentation using coarse supervision O Saha, Z Cheng, S Maji European Conference on Computer Vision, 283-299, 2022 | 10 | 2022 |
Edgeml: machine learning for resource-constrained edge devices (2020) DK Dennis, Y Gaurkar, S Gopinath, S Goyal, C Gupta, M Jain, S Jaiswal URL https://github. com/Microsoft/EdgeML, 0 | 6 | |
Do events change opinions on social media? Studying the 2016 us presidential debates S Khosla, N Chhaya, S Jindal, O Saha, M Srivastava Social Informatics: 11th International Conference, SocInfo 2019, Doha, Qatar …, 2019 | 5 | 2019 |
RecSal: Deep Recursive Supervision for Visual Saliency Prediction S Mishra, O Saha British Machine Vision Conference, 2020 | 3 | 2020 |
NTIRE 2024 Quality Assessment of AI-Generated Content Challenge X Liu, X Min, G Zhai, C Li, T Kou, W Sun, H Wu, Y Gao, Y Cao, Z Zhang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
Improved Zero-Shot Classification by Adapting VLMs with Text Descriptions O Saha, G Van Horn, S Maji Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
YouDream: Generating Anatomically Controllable Consistent Text-to-3D Animals S Mishra, O Saha, AC Bovik arXiv preprint arXiv:2406.16273, 2024 | | 2024 |
Decomposed evaluations of geographic disparities in text-to-image models A Sureddy, D Padalia, N Periyakaruppa, O Saha, A Williams, ... arXiv preprint arXiv:2406.11988, 2024 | | 2024 |
C3DAG: Controlled 3D Animal Generation using 3D pose guidance S Mishra, O Saha, AC Bovik arXiv preprint arXiv:2406.07742, 2024 | | 2024 |
PARTICLE: Part Discovery and Contrastive Learning for Fine-grained Recognition O Saha, S Maji Proceedings of the IEEE/CVF International Conference on Computer Vision, 167-176, 2023 | | 2023 |