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Lovekesh Vig
Lovekesh Vig
TCS Research
Bestätigte E-Mail-Adresse bei tcs.com
Titel
Zitiert von
Zitiert von
Jahr
Long Short Term Memory Networks for Anomaly Detection in Time Series.
P Malhotra, L Vig, G Shroff, P Agarwal
Esann 2015, 89, 2015
16782015
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
12042016
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
4822015
Multi-robot coalition formation
L Vig, JA Adams
IEEE transactions on robotics 22 (4), 637-649, 2006
3792006
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
2562016
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
2072017
Tablenet: Deep learning model for end-to-end table detection and tabular data extraction from scanned document images
SS Paliwal, D Vishwanath, R Rahul, M Sharma, L Vig
2019 International Conference on Document Analysis and Recognition (ICDAR …, 2019
1872019
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
1862017
Sequence and time aware neighborhood for session-based recommendations: Stan
D Garg, P Gupta, P Malhotra, L Vig, G Shroff
Proceedings of the 42nd international ACM SIGIR conference on research and …, 2019
1222019
Coalition formation: From software agents to robots
L Vig, JA Adams
Journal of Intelligent and Robotic Systems 50, 85-118, 2007
1082007
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
1012017
Online anomaly detection with concept drift adaptation using recurrent neural networks
S Saurav, P Malhotra, V TV, N Gugulothu, L Vig, P Agarwal, G Shroff
Proceedings of the acm india joint international conference on data science …, 2018
982018
Convtimenet: A pre-trained deep convolutional neural network for time series classification
K Kashiparekh, J Narwariya, P Malhotra, L Vig, G Shroff
2019 international joint conference on neural networks (IJCNN), 1-8, 2019
962019
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
932017
An efficient end-to-end neural model for handwritten text recognition
A Chowdhury, L Vig
arXiv preprint arXiv:1807.07965, 2018
872018
LSTM-based encoder-decoder for multi-sensor anomaly detection. arXiv 2016
P Malhotra, A Ramakrishnan, G Anand, L Vig, P Agarwal, G Shroff
arXiv preprint arXiv:1607.00148, 2016
872016
Market-based multi-robot coalition formation
L Vig, JA Adams
Distributed Autonomous Robotic Systems 7, 227-236, 2006
822006
A comparison of shallow and deep learning methods for predicting cognitive performance of stroke patients from MRI lesion images
S Chauhan, L Vig, M De Filippo De Grazia, M Corbetta, S Ahmad, M Zorzi
Frontiers in neuroinformatics 13, 53, 2019
792019
Anomaly detection system and method
P Malhotra, G Shroff, P Agarwal, L Vig
US Patent 10,223,403, 2019
782019
Meta-dermdiagnosis: Few-shot skin disease identification using meta-learning
K Mahajan, M Sharma, L Vig
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
752020
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