Lovekesh Vig
Lovekesh Vig
TCS Research
Verified email at tcs.com
Title
Cited by
Cited by
Year
Long short term memory networks for anomaly detection in time series
P Malhotra, L Vig, G Shroff, P Agarwal
Proceedings 89, 89-94, 2015
6912015
Multi-robot coalition formation
L Vig, JA Adams
IEEE transactions on robotics 22 (4), 637-649, 2006
3132006
LSTM-based encoder-decoder for multi-sensor anomaly detection
P Malhotra, A Ramakrishnan, G Anand, L Vig, P Agarwal, G Shroff
arXiv preprint arXiv:1607.00148, 2016
2972016
Anomaly detection in ECG time signals via deep long short-term memory networks
S Chauhan, L Vig
2015 IEEE International Conference on Data Science and Advanced Analytics …, 2015
2132015
Multi-sensor prognostics using an unsupervised health index based on LSTM encoder-decoder
P Malhotra, V TV, A Ramakrishnan, G Anand, L Vig, P Agarwal, G Shroff
arXiv preprint arXiv:1608.06154, 2016
1062016
Coalition formation: From software agents to robots
L Vig, JA Adams
Journal of Intelligent and Robotic Systems 50 (1), 85-118, 2007
902007
Market-based multi-robot coalition formation
L Vig, JA Adams
Distributed Autonomous Robotic Systems 7, 227-236, 2006
692006
Predicting remaining useful life using time series embeddings based on recurrent neural networks
N Gugulothu, V Tv, P Malhotra, L Vig, P Agarwal, G Shroff
arXiv preprint arXiv:1709.01073, 2017
682017
TimeNet: Pre-trained deep recurrent neural network for time series classification
P Malhotra, V TV, L Vig, P Agarwal, G Shroff
arXiv preprint arXiv:1706.08838, 2017
632017
Issues in multi-robot coalition formation
L Vig, JA Adams
Multi-Robot Systems. From Swarms to Intelligent Automata Volume III, 15-26, 2005
482005
Printer system for vertical or horizontal mounting
IIWR Sides
US Patent 6,824,129, 2004
40*2004
Using convolutional neural networks to discover cogntively validated features for gender classification
A Verma, L Vig
2014 International Conference on Soft Computing and Machine Intelligence, 33-37, 2014
272014
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
252017
An efficient end-to-end neural model for handwritten text recognition
A Chowdhury, L Vig
arXiv preprint arXiv:1807.07965, 2018
242018
Siamese networks for chromosome classification
S Jindal, G Gupta, M Yadav, M Sharma, L Vig
Proceedings of the IEEE International Conference on Computer Vision …, 2017
232017
Transfer learning for clinical time series analysis using recurrent neural networks
P Gupta, P Malhotra, L Vig, G Shroff
arXiv preprint arXiv:1807.01705, 2018
222018
An ar inspection framework: Feasibility study with multiple ar devices
P Ramakrishna, E Hassan, R Hebbalaguppe, M Sharma, G Gupta, L Vig, ...
2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR …, 2016
222016
Non-additive multi-objective robot coalition formation
M Agarwal, N Kumar, L Vig
Expert Systems with Applications 41 (8), 3736-3747, 2014
222014
A Framework for Multi-Robot Coalition Formation.
L Vig, JA Adams
IICAI, 347-363, 2005
222005
Pedestrian detection via mixture of CNN experts and thresholded aggregated channel features
A Verma, R Hebbalaguppe, L Vig, S Kumar, E Hassan
Proceedings of the IEEE International Conference on Computer Vision …, 2015
192015
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