Sourav Bhattacharya

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Nicholas LaneUniversity of Cambridge and Flower LabsDirección de correo verificada de cam.ac.uk
Fahim KawsarBell Labs and University of GlasgowDirección de correo verificada de nokia-bell-labs.com
Petteri NurmiProfessor of Computer Science, University of HelsinkiDirección de correo verificada de helsinki.fi
Petko GeorgievGoogle DeepMind, University of CambridgeDirección de correo verificada de cam.ac.uk
Alberto Gil C. P. RamosSamsung Electronics (AI Center)Dirección de correo verificada de samsung.com
Mikkel Baun KjærgaardProfessor in Software Engineering, University of Southern DenmarkDirección de correo verificada de mmmi.sdu.dk
Akhil MathurMeta AIDirección de correo verificada de meta.com
Henrik BlunckProfessor of Computer Science, University of Applied Sciences Bochum, GermanyDirección de correo verificada de hs-bochum.de
Cecilia MascoloUniversity of CambridgeDirección de correo verificada de cl.cam.ac.uk
Lei JiaoUniversity of OregonDirección de correo verificada de uoregon.edu
Łukasz DudziakSamsung AI Center CambridgeDirección de correo verificada de samsung.com
Abhinav MehrotraSamsung AI CenterDirección de correo verificada de samsung.com
Thor Siiger PrentowPhD Student, Aarhus UniversityDirección de correo verificada de prentow.dk
Tobias SonneResearch Associate, UCLIC, University College London - Supported by the Carlsberg FoundationDirección de correo verificada de ucl.ac.uk
Mads Møller JensenLEGO GroupDirección de correo verificada de mmjensen.com
Anind K. DeyUniversity of WashingtonDirección de correo verificada de uw.edu
Ravichander VipperlaSenior Applied Scientist, Amazon, Cambridge, UKDirección de correo verificada de amazon.com
Mahesh K. MarinaSchool of Informatics, The University of EdinburghDirección de correo verificada de inf.ed.ac.uk
Valentin RaduUniversity of SheffieldDirección de correo verificada de shef.ac.uk
N. AsokanProfessor of Computer Science, University of WaterlooDirección de correo verificada de uwaterloo.ca

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Sourav Bhattacharya

Samsung AI

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On-device ML Generative AI Embedded deep Learning Machine Learning Mobile Sensing


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	868	2015
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	665	2016
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	317	2018
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	295	2016
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	290	2015
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	247	2017
From Smart to Deep: Robust Activity Recognition on Smartwatches using Deep Learning S Bhattacharya, ND Lane	203	2016
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	182	2017
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	173	2016
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	146	2014
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	124	2011
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	117	2006
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	109	2019
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	90	2014
Identifying meaningful places: The non-parametric way P Nurmi, S Bhattacharya Pervasive Computing: 6th International Conference, Pervasive 2008 Sydney …, 2008	90	2008
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	85	2017
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	82	2018
NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition A Mehrotra, AGCP Ramos, S Bhattacharya, Ł Dudziak, R Vipperla, ... International Conference on Learning Representations (ICLR), 2021	81	2021
Robust and Energy-Efficient Trajectory Tracking for Mobile Devices S Bhattacharya, H Blunck, MB Kjærgaard, P Nurmi IEEE Transactions on Mobile Computing, 2014	50	2014
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	50	2010

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