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Sharada Prasanna Mohanty
Sharada Prasanna Mohanty
AIcrowd SA, Switzerland
Bestätigte E-Mail-Adresse bei epfl.ch - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Using deep learning for image-based plant disease detection
SP Mohanty, DP Hughes, M Salathé
Frontiers in plant science 7, 1419, 2016
41022016
Deep learning for understanding satellite imagery: An experimental survey
SP Mohanty, J Czakon, KA Kaczmarek, A Pyskir, P Tarasiewicz, S Kunwar, ...
Frontiers in Artificial Intelligence 3, 534696, 2020
1172020
Deep learning for understanding satellite imagery: An experimental survey
SP Mohanty, J Czakon, KA Kaczmarek, A Pyskir, P Tarasiewicz, S Kunwar, ...
Frontiers in Artificial Intelligence 3, 534696, 2020
1172020
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
Ł Kidziński, SP Mohanty, CF Ong, Z Huang, S Zhou, A Pechenko, ...
The NIPS'17 Competition: Building Intelligent Systems, 121-153, 2018
1002018
Learning to run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning
Ł Kidziński, SP Mohanty, CF Ong, JL Hicks, SF Carroll, S Levine, ...
The NIPS'17 Competition: Building Intelligent Systems, 101-120, 2018
802018
The minerl competition on sample efficient reinforcement learning using human priors
WH Guss, C Codel, K Hofmann, B Houghton, N Kuno, S Milani, ...
arXiv preprint arXiv:1904.10079 2, 2019
762019
Critical dynamics in population vaccinating behavior
AD Pananos, TM Bury, C Wang, J Schonfeld, SP Mohanty, B Nyhan, ...
Proceedings of the National Academy of Sciences 114 (52), 13762-13767, 2017
752017
Flatland-RL: Multi-Agent Reinforcement Learning on Trains
S Mohanty, E Nygren, F Laurent, M Schneider, C Scheller, ...
arXiv preprint arXiv:2012.05893, 2020
742020
Adversarial vision challenge
W Brendel, J Rauber, A Kurakin, N Papernot, B Veliqi, SP Mohanty, ...
The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020
662020
Adversarial vision challenge
W Brendel, J Rauber, A Kurakin, N Papernot, B Veliqi, SP Mohanty, ...
The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020
662020
Using 2D video-based pose estimation for automated prediction of autism spectrum disorders in young children
N Kojovic, S Natraj, SP Mohanty, T Maillart, M Schaer
Scientific Reports 11 (1), 15069, 2021
632021
Artificial intelligence for prosthetics: Challenge solutions
Ł Kidziński, C Ong, SP Mohanty, J Hicks, S Carroll, B Zhou, H Zeng, ...
The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020
522020
Artificial intelligence for prosthetics: Challenge solutions
Ł Kidziński, C Ong, SP Mohanty, J Hicks, S Carroll, B Zhou, H Zeng, ...
The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020
522020
The multi-agent behavior dataset: Mouse dyadic social interactions
JJ Sun, T Karigo, D Chakraborty, SP Mohanty, B Wild, Q Sun, C Chen, ...
Advances in neural information processing systems 2021 (DB1), 1, 2021
512021
The Multi-Agent Reinforcement Learning in Malm\" O (MARL\" O) Competition
D Perez-Liebana, K Hofmann, SP Mohanty, N Kuno, A Kramer, S Devlin, ...
arXiv preprint arXiv:1901.08129, 2019
432019
The Multi-Agent Reinforcement Learning in Malm\" O (MARL\" O) Competition
D Perez-Liebana, K Hofmann, SP Mohanty, N Kuno, A Kramer, S Devlin, ...
arXiv preprint arXiv:1901.08129, 2019
432019
The food recognition benchmark: Using deep learning to recognize food in images
SP Mohanty, G Singhal, EA Scuccimarra, D Kebaili, H Héritier, ...
Frontiers in Nutrition 9, 875143, 2022
352022
The MineRL 2019 competition on sample efficient reinforcement learning using human priors
WH Guss, C Codel, K Hofmann, B Houghton, N Kuno, S Milani, ...
arXiv preprint arXiv:1904.10079, 2019
342019
Crowdai mapping challenge 2018: Baseline with mask rcnn
SP Mohanty
GitHub Repository, 2018
342018
Retrospective analysis of the 2019 minerl competition on sample efficient reinforcement learning
S Milani, N Topin, B Houghton, WH Guss, SP Mohanty, K Nakata, ...
NeurIPS 2019 Competition and Demonstration Track, 203-214, 2020
33*2020
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