kishore reddy konda
kishore reddy konda
Verified email at
TitleCited byYear
Combining modality specific deep neural networks for emotion recognition in video
SE Kahou, C Pal, X Bouthillier, P Froumenty, Ç Gülçehre, R Memisevic, ...
Proceedings of the 15th ACM on International conference on multimodal …, 2013
Emonets: Multimodal deep learning approaches for emotion recognition in video
SE Kahou, X Bouthillier, P Lamblin, C Gulcehre, V Michalski, K Konda, ...
Journal on Multimodal User Interfaces 10 (2), 99-111, 2016
Recurrent neural networks for emotion recognition in video
S Ebrahimi Kahou, V Michalski, K Konda, R Memisevic, C Pal
Proceedings of the 2015 ACM on International Conference on Multimodal …, 2015
Learning visual odometry with a convolutional network.
KR Konda, R Memisevic
VISAPP (1), 486-490, 2015
Modeling deep temporal dependencies with recurrent grammar cells""
V Michalski, R Memisevic, K Konda
Advances in neural information processing systems, 1925-1933, 2014
Zero-bias autoencoders and the benefits of co-adapting features
K Konda, R Memisevic, D Krueger
International conference on learning representations, 2015
Dropout as data augmentation
K Konda, X Bouthillier, R Memisevic, P Vincent
stat 1050, 29, 2015
A unified approach to learning depth and motion features
K Konda, R Memisevic
Proceedings of the 2014 Indian Conference on Computer Vision Graphics and …, 2014
Real time interaction with mobile robots using hand gestures
KR Konda, A Königs, H Schulz, D Schulz
Proceedings of the seventh annual ACM/IEEE international conference on Human …, 2012
The role of spatio-temporal synchrony in the encoding of motion.
KR Konda, R Memisevic, V Michalski
ICLR, 2014
How far can we go without convolution: Improving fully-connected networks
Z Lin, R Memisevic, K Konda
International conference in learning representations Workshop Track, 2016
Real-time activity recognition via deep learning of motion features
K Konda, P Chandrashekhariah, R Memisevic, J Triesch
Proceedings, 427, 2015
Only sparsity based loss function for learning representations
V Bakaraju, KR Konda
arXiv preprint arXiv:1903.02893, 2019
Building effective deep neural networks one feature at a time
M Mundt, T Weis, K Konda, V Ramesh
Building effective deep neural network architectures one feature at a time
M Mundt, T Weis, K Konda, V Ramesh
arXiv preprint arXiv:1705.06778, 2017
Unsupervised relational feature learning for vision
KR Konda
Goethe University Frankfurt, 2016
The system can't perform the operation now. Try again later.
Articles 1–16