Cikkek nyilvánosan hozzáférhető megbízással - Aditya KhoslaTovábbi információ
Valahol hozzáférhető: 8
Learning deep features for discriminative localization
B Zhou, A Khosla, A Lapedriza, A Oliva, A Torralba
Proceedings of the IEEE conference on computer vision and pattern …, 2016
Megbízások: US National Science Foundation
3d shapenets: A deep representation for volumetric shapes
Z Wu, S Song, A Khosla, F Yu, L Zhang, X Tang, J Xiao
Proceedings of the IEEE conference on computer vision and pattern …, 2015
Megbízások: Research Grants Council, Hong Kong
Places: A 10 million image database for scene recognition
B Zhou, A Lapedriza, A Khosla, A Oliva, A Torralba
IEEE transactions on pattern analysis and machine intelligence 40 (6), 1452-1464, 2017
Megbízások: US National Science Foundation, US Department of Defense
Network dissection: Quantifying interpretability of deep visual representations
D Bau, B Zhou, A Khosla, A Oliva, A Torralba
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Megbízások: US National Science Foundation, US Department of Defense
Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence
RM Cichy, A Khosla, D Pantazis, A Torralba, A Oliva
Scientific reports 6 (1), 27755, 2016
Megbízások: US National Science Foundation, US National Institutes of Health, German …
Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes
JA Diao, JK Wang, WF Chui, V Mountain, SC Gullapally, R Srinivasan, ...
Nature communications 12 (1), 1613, 2021
Megbízások: US National Institutes of Health
Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks
RM Cichy, A Khosla, D Pantazis, A Oliva
NeuroImage 153, 346-358, 2017
Megbízások: US National Science Foundation, US National Institutes of Health
Visualizing object detection features
C Vondrick, A Khosla, H Pirsiavash, T Malisiewicz, A Torralba
International Journal of Computer Vision 119, 145-158, 2016
Megbízások: US National Science Foundation
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