Dipesh Tamboli
Dipesh Tamboli
Applied Scientist @ Amazon Robotics | Purdue | IITB
Verified email at - Homepage
Cited by
Cited by
Multi-source open-set deep adversarial domain adaptation
S Rakshit, D Tamboli, PS Meshram, B Banerjee, G Roig, S Chaudhuri
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Breast cancer histopathology image classification and localization using multiple instance learning
A Patil, D Tamboli, S Meena, D Anand, A Sethi
2019 IEEE International WIE conference on electrical and computer …, 2019
Fast design of plasmonic metasurfaces enabled by deep learning
A Mall, A Patil, D Tamboli, A Sethi, A Kumar
Journal of Physics D: Applied Physics 53 (49), 49LT01, 2020
Image-based phenotyping of diverse rice (Oryza Sativa L.) genotypes
MK Vishal, D Tamboli, A Patil, R Saluja, B Banerjee, A Sethi, D Raju, ...
arXiv preprint arXiv:2004.02498, 2020
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning
J Chen, D Tamboli, T Lan, V Aggarwal
Proceedings of the 40th International Conference on Machine Learning, 4895-4920, 2023
Saliency-driven class impressions for feature visualization of deep neural networks
D Tamboli, S Addepalli, RV Babu, B Banerjee
2020 IEEE International Conference on Image Processing (ICIP), 1936-1940, 2020
RSINet: Inpainting Remotely Sensed Images Using Triple GAN Framework
D Tamboli, A Kumar, S Pande, B Banerjee
IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022
Image-Based Phenotyping of Diverse Rice
MK Vishal, D Tamboli, A Patil, R Saluja, B Banerjee, A Sethi, D Raju, ...
Oryza sativa, 0
Prediction of the color change of surface thermally treated wood by artificial neural network
J Mo, D Tamboli, E Haviarova
European Journal of Wood and Wood Products, 1-12, 2023
Thermally Treated to Perfection: Enhancing Wood Color and Properties with Surface Thermal Treatment
J Mo, D Tamboli, E Haviarova
Kuiper: Moderated Asynchronous Federated Learning on Heterogeneous Mobile Devices with Non-IID Data
D Tamboli, P Jain, A Sharma, B Banerjee, S Bagchi, S Chaterji
Explaining decision of model from its prediction
D Tamboli
arXiv preprint arXiv:2106.08366, 2021
Supplementary materials for paper” Multi-Source open-set deep adversarial domain adaptation”
S Rakshit, D Tamboli, P Shuddhodhan, BB Meshram, G Roig, ...
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