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Sourav Bhattacharya
Sourav Bhattacharya
Samsung AI
Verified email at samsung.com
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Cited by
Year
DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices
ND Lane, S Bhattacharya, P Georgiev, C Forlivesi, L Jiao, L Qendro, ...
International Conference on Information Processing in Sensor Networks (IPSN '16), 2016
4722016
Smart Devices are Different: Assessing and Mitigating Mobile Sensing Heterogeneities for Activity Recognition
A Stisen, H Blunck, S Bhattacharya, TS Prentow, MB Kjærgaard, A Dey, ...
The 13th ACM Conference on Embedded Networked Sensor Systems, 2015
4672015
An Early Resource Characterization of Deep Learning on Wearables, Smartphones and Internet-of-Things Devices
ND Lane, S Bhattacharya, P Georgiev, C Forlivesi, F Kawsar
Proceedings of the 2015 International Workshop on Internet of Things towards …, 2015
2302015
Sparsification and Separation of Deep Learning Layers for Constrained Resource Inference on Wearables
S Bhattacharya, ND Lane
ACM Conference on Embedded Networked Sensor Systems (SenSys) 2016, 2016
1952016
Multimodal Deep Learning for Activity and Context Recognition
V Radu, C Tong, S Bhattacharya, ND Lane, C Mascolo, MK Marina, ...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018
1802018
Squeezing deep learning into mobile and embedded devices
ND Lane, S Bhattacharya, A Mathur, P Georgiev, C Forlivesi, F Kawsar
IEEE Pervasive Computing 16 (3), 82-88, 2017
1782017
From Smart to Deep: Robust Activity Recognition on Smartwatches using Deep Learning
S Bhattacharya, ND Lane
1602016
Towards multimodal deep learning for activity recognition on mobile devices
V Radu, ND Lane, S Bhattacharya, C Mascolo, MK Marina, F Kawsar
Proceedings of the 2016 ACM International Joint Conference on Pervasive and …, 2016
1292016
Using unlabeled data in a sparse-coding framework for human activity recognition
S Bhattacharya, P Nurmi, N Hammerla, T Plötz
Pervasive and Mobile Computing 15, 242-262, 2014
1232014
Energy-efficient trajectory tracking for mobile devices
MB Kjærgaard, S Bhattacharya, H Blunck, P Nurmi
Proceedings of the 9th international conference on Mobile systems …, 2011
1212011
DeepEye: Resource Efficient Local Execution of Multiple Deep Vision Models using Wearable Commodity Hardware
A Mathur, ND Lane, S Bhattacharya, A Boran, C Forlivesi, F Kawsar
The 15th International Conference on Mobile Systems, Applications and …, 2017
1132017
A survey on different video watermarking techniques and comparative analysis with reference to H. 264/AVC
S Bhattacharya, T Chattopadhyay, A Pal
2006 IEEE International Symposium on Consumer Electronics, 1-6, 2006
1092006
Identifying meaningful places: The non-parametric way
P Nurmi, S Bhattacharya
International Conference on Pervasive Computing, 111-127, 2008
912008
The company you keep: mobile malware infection rates and inexpensive risk indicators
HTT Truong, E Lagerspetz, P Nurmi, AJ Oliner, S Tarkoma, N Asokan, ...
Proceedings of the 23rd international conference on World wide web, 39-50, 2014
832014
Low-resource Multi-task Audio Sensing for Mobile and Embedded Devices via Shared Deep Neural Network Representations
P Georgiev, S Bhattacharya, N Lane, C Mascolo
Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2017
492017
Robust and Energy-Efficient Trajectory Tracking for Mobile Devices
S Bhattacharya, H Blunck, MB Kjærgaard, P Nurmi
IEEE Transactions on Mobile Computing, 2014
482014
A grid-based algorithm for on-device GSM positioning
P Nurmi, S Bhattacharya, J Kukkonen
Proceedings of the 12th ACM international conference on Ubiquitous computing …, 2010
462010
Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices
A Mathur, T Zhang, S Bhattacharya, P Veličković, L Joffe, ND Lane, ...
Proceedings of the 17th ACM/IEEE International Conference on Information …, 2018
452018
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors
R Lee, SI Venieris, L Dudziak, S Bhattacharya, ND Lane
The 25th Annual International Conference on Mobile Computing and Networking …, 2019
402019
DXTK: Enabling Resource-efficient Deep Learning on Mobile and Embedded Devices with the DeepX Toolkit.
ND Lane, S Bhattacharya, A Mathur, C Forlivesi, F Kawsar
MobiCASE, 98-107, 2016
302016
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