| Emotion recognition in the wild challenge 2014: Baseline, data and protocol A Dhall, R Goecke, J Joshi, K Sikka, T Gedeon Proceedings of the 16th international conference on multimodal interaction …, 2014 | 155 | 2014 |
| A fully automated algorithm under modified FCM framework for improved brain MR image segmentation K Sikka, N Sinha, PK Singh, AK Mishra Magnetic Resonance Imaging 27 (7), 994-1004, 2009 | 131 | 2009 |
| Adascan: Adaptive scan pooling in deep convolutional neural networks for human action recognition in videos A Kar, N Rai, K Sikka, G Sharma Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 87 | 2017 |
| Exploring bag of words architectures in the facial expression domain K Sikka, T Wu, J Susskind, M Bartlett European Conference on Computer Vision, 250-259, 2012 | 87 | 2012 |
| Zero-shot object detection A Bansal, K Sikka, G Sharma, R Chellappa, A Divakaran Proceedings of the European Conference on Computer Vision (ECCV), 384-400, 2018 | 77 | 2018 |
| Automated assessment of children’s postoperative pain using computer vision K Sikka, AA Ahmed, D Diaz, MS Goodwin, KD Craig, MS Bartlett, ... Pediatrics 136 (1), e124-e131, 2015 | 76 | 2015 |
| Multiple kernel learning for emotion recognition in the wild K Sikka, K Dykstra, S Sathyanarayana, G Littlewort, M Bartlett Proceedings of the 15th ACM on International conference on multimodal …, 2013 | 73 | 2013 |
| Weakly supervised pain localization using multiple instance learning K Sikka, A Dhall, M Bartlett 2013 10th IEEE International Conference and Workshops on Automatic Face and …, 2013 | 65 | 2013 |
| The more the merrier: Analysing the affect of a group of people in images A Dhall, J Joshi, K Sikka, R Goecke, N Sebe 2015 11th IEEE international conference and workshops on automatic face and …, 2015 | 64 | 2015 |
| Lomo: Latent ordinal model for facial analysis in videos K Sikka, G Sharma, M Bartlett Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 49 | 2016 |
| Classification and weakly supervised pain localization using multiple segment representation K Sikka, A Dhall, MS Bartlett Image and vision computing 32 (10), 659-670, 2014 | 44 | 2014 |
| An adaptive fuzzy c-means clustering-based mixtures of experts model for unlabeled data classification HJ Xing, BG Hu Neurocomputing 71 (4-6), 1008-1021, 2008 | 43 | 2008 |
| Deep Q-learning for Active Recognition of GERMS: Baseline performance on a standardized dataset for active learning. M Malmir, K Sikka, D Forster, JR Movellan, G Cottrell BMVC, 161.1-161.11, 2015 | 31* | 2015 |
| Exemplar hidden markov models for classification of facial expressions in videos K Sikka, A Dhall, M Bartlett Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 24 | 2015 |
| Deep active object recognition by joint label and action prediction M Malmir, K Sikka, D Forster, I Fasel, JR Movellan, GW Cottrell Computer Vision and Image Understanding 156, 128-137, 2017 | 18 | 2017 |
| Joint Clustering and Classification for Multiple Instance Learning K Sikka, R Giri, M Bartlett British Machine Vision Conference, 71.1-71.12, 2015 | 13 | 2015 |
| Align2ground: Weakly supervised phrase grounding guided by image-caption alignment S Datta, K Sikka, A Roy, K Ahuja, D Parikh, A Divakaran Proceedings of the IEEE International Conference on Computer Vision, 2601-2610, 2019 | 11 | 2019 |
| Facial expression analysis for estimating pain in clinical settings K Sikka Proceedings of the 16th International Conference on Multimodal Interaction …, 2014 | 9 | 2014 |
| Integrating text and image: determining multimodal document intent in instagram posts J Kruk, J Lubin, K Sikka, X Lin, D Jurafsky, A Divakaran arXiv preprint arXiv:1904.09073, 2019 | 8 | 2019 |
| Understanding visual ads by aligning symbols and objects using co-attention K Ahuja, K Sikka, A Roy, A Divakaran arXiv preprint arXiv:1807.01448, 2018 | 6 | 2018 |
Marian Stewart BartlettApple Inc (Formerly Emotient Inc & UCSD)Verified email at salk.edu
