| CASAS: A smart home in a box DJ Cook, AS Crandall, BL Thomas, NC Krishnan Computer 46 (7), 62-69, 2012 | 1008 | 2012 |
| Activity recognition on streaming sensor data NC Krishnan, DJ Cook Pervasive and mobile computing 10, 138-154, 2014 | 703 | 2014 |
| Transfer learning for activity recognition: A survey D Cook, KD Feuz, NC Krishnan Knowledge and information systems 36 (3), 537-556, 2013 | 593 | 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 | 438 | 2012 |
| Activity discovery and activity recognition: A new partnership DJ Cook, NC Krishnan, P Rashidi IEEE transactions on cybernetics 43 (3), 820-828, 2013 | 317 | 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 | 298 | 2016 |
| Activity learning: discovering, recognizing, and predicting human behavior from sensor data DJ Cook, NC Krishnan John Wiley & Sons, 2015 | 237 | 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 | 158 | 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 | 141 | 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 | 107 | 2019 |
| 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 | 107 | 2008 |
| 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 | 89 | 2016 |
| 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 | 82 | 2009 |
| Machine learning methods trained on simple models can predict critical transitions in complex natural systems S Deb, S Sidheekh, CF Clements, NC Krishnan, PS Dutta Royal Society Open Science 9 (2), 211475, 2022 | 67 | 2022 |
| Mining the home environment DJ Cook, N Krishnan Journal of intelligent information systems 43 (3), 503-519, 2014 | 66 | 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 | 65 | 2018 |
| Wheat crop yield prediction using deep LSTM model S Sharma, S Rai, NC Krishnan arXiv preprint arXiv:2011.01498, 2020 | 64 | 2020 |
| 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 | 61 | 2013 |
| Supervised Heterogeneous Domain Adaptation via Random Forests S Sukhija, NC Krishnan, G Singh International Joint Conference on Artificial Intelligence, 2039-2045, 2016 | 44 | 2016 |
| Bandwidth sharing for relaying in cellular systems N Krishnan, RD Yates, NB Mandayam, JS Panchal IEEE Transactions on Wireless Communications 11 (1), 117-129, 2011 | 43 | 2011 |
Diane J CookWashington State UniversityVerified email at eecs.wsu.edu
