CASAS: A smart home in a box DJ Cook, AS Crandall, BL Thomas, NC Krishnan Computer 46 (7), 62-69, 2012 | 912 | 2012 |
Activity recognition on streaming sensor data NC Krishnan, DJ Cook Pervasive and mobile computing 10, 138-154, 2014 | 678 | 2014 |
Transfer learning for activity recognition: A survey D Cook, KD Feuz, NC Krishnan Knowledge and information systems 36, 537-556, 2013 | 535 | 2013 |
Simple and complex activity recognition through smart phones S Dernbach, B Das, NC Krishnan, BL Thomas, DJ Cook 2012 eighth international conference on intelligent environments, 214-221, 2012 | 450 | 2012 |
Activity discovery and activity recognition: A new partnership DJ Cook, NC Krishnan, P Rashidi IEEE transactions on cybernetics 43 (3), 820-828, 2013 | 304 | 2013 |
Spotgarbage: smartphone app to detect garbage using deep learning G Mittal, KB Yagnik, M Garg, NC Krishnan Proceedings of the 2016 ACM International Joint Conference on Pervasive and …, 2016 | 257 | 2016 |
Activity learning: discovering, recognizing, and predicting human behavior from sensor data DJ Cook, NC Krishnan John Wiley & Sons, 2015 | 217 | 2015 |
RACOG and wRACOG: Two probabilistic oversampling techniques B Das, NC Krishnan, DJ Cook IEEE transactions on knowledge and data engineering 27 (1), 222-234, 2014 | 136 | 2014 |
Analysis of low resolution accelerometer data for continuous human activity recognition NC Krishnan, S Panchanathan 2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008 | 134 | 2008 |
Real time human activity recognition using tri-axial accelerometers NC Krishnan, D Colbry, C Juillard, S Panchanathan Sensors, signals and information processing workshop 2008, 3337-3340, 2008 | 101 | 2008 |
Semantically aligned bias reducing zero shot learning A Paul, NC Krishnan, P Munjal Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 90 | 2019 |
Recognition of hand movements using wearable accelerometers NC Krishnan, C Juillard, D Colbry, S Panchanathan Journal of Ambient Intelligence and Smart Environments 1 (2), 143-155, 2009 | 78 | 2009 |
One-class classification-based real-time activity error detection in smart homes B Das, DJ Cook, NC Krishnan, M Schmitter-Edgecombe IEEE journal of selected topics in signal processing 10 (5), 914-923, 2016 | 77 | 2016 |
Mining the home environment DJ Cook, N Krishnan Journal of intelligent information systems 43, 503-519, 2014 | 65 | 2014 |
Multi-task deep learning for predicting poverty from satellite images S Pandey, T Agarwal, NC Krishnan Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 57 | 2018 |
Handling class overlap and imbalance to detect prompt situations in smart homes B Das, NC Krishnan, DJ Cook 2013 IEEE 13th international conference on data mining workshops, 266-273, 2013 | 53 | 2013 |
Wheat crop yield prediction using deep LSTM model S Sharma, S Rai, NC Krishnan arXiv preprint arXiv:2011.01498, 2020 | 51 | 2020 |
Supervised Heterogeneous Domain Adaptation via Random Forests S Sukhija, NC Krishnan, G Singh International Joint Conference on Artificial Intelligence, 2039-2045, 2016 | 44 | 2016 |
Topology preserving domain adaptation for addressing subject based variability in semg signal R Chattopadhyay, NC Krishnan, S Panchanathan 2011 AAAI Spring symposium series, 2011 | 40 | 2011 |
Measuring movement expertise in surgical tasks K Kahol, NC Krishnan, VN Balasubramanian, S Panchanathan, M Smith, ... Proceedings of the 14th ACM international conference on Multimedia, 719-722, 2006 | 39 | 2006 |