| Fusing audio, visual and textual clues for sentiment analysis from multimodal content S Poria, E Cambria, N Howard, GB Huang, A Hussain Neurocomputing 174, 50-59, 2016 | 362 | 2016 |
| Enhanced SenticNet with affective labels for concept-based opinion mining S Poria, A Gelbukh, A Hussain, N Howard, D Das, S Bandyopadhyay IEEE Intelligent Systems 28 (2), 31-38, 2013 | 208 | 2013 |
| Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis S Poria, H Peng, A Hussain, N Howard, E Cambria Neurocomputing 261, 217-230, 2017 | 120 | 2017 |
| Semantic multidimensional scaling for open-domain sentiment analysis E Cambria, Y Song, H Wang, N Howard IEEE intelligent systems 29 (2), 44-51, 2012 | 118 | 2012 |
| Metaphor identification in large texts corpora Y Neuman, D Assaf, Y Cohen, M Last, S Argamon, N Howard, O Frieder PloS one 8 (4), e62343, 2013 | 110 | 2013 |
| Comparing oversampling techniques to handle the class imbalance problem: A customer churn prediction case study A Amin, S Anwar, A Adnan, M Nawaz, N Howard, J Qadir, A Hawalah, ... IEEE Access 4, 7940-7957, 2016 | 107 | 2016 |
| Intention awareness: improving upon situation awareness in human-centric environments N Howard, E Cambria Human-centric Computing and Information Sciences 3 (1), 1-17, 2013 | 94 | 2013 |
| Common sense knowledge based personality recognition from text S Poria, A Gelbukh, B Agarwal, E Cambria, N Howard Mexican International Conference on Artificial Intelligence, 484-496, 2013 | 92 | 2013 |
| Dependency-based semantic parsing for concept-level text analysis S Poria, B Agarwal, A Gelbukh, A Hussain, N Howard International Conference on Intelligent Text Processing and Computational …, 2014 | 70 | 2014 |
| The use of photoplethysmography for assessing hypertension M Elgendi, R Fletcher, Y Liang, N Howard, NH Lovell, D Abbott, K Lim, ... NPJ digital medicine 2 (1), 1-11, 2019 | 61 | 2019 |
| Cognitive intelligence: deep learning, thinking, and reasoning by brain-inspired systems Y Wang, B Widrow, LA Zadeh, N Howard, S Wood, VC Bhavsar, G Budin, ... International Journal of Cognitive Informatics and Natural Intelligence …, 2016 | 56 | 2016 |
| Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics E Cambria, N Howard, J Hsu, A Hussain 2013 IEEE symposium on computational intelligence for human-like …, 2013 | 53 | 2013 |
| Automatic identification of conceptual metaphors with limited knowledge L Gandy, N Allan, M Atallah, O Frieder, N Howard, S Kanareykin, ... Proceedings of the AAAI Conference on Artificial Intelligence 27 (1), 2013 | 44 | 2013 |
| Music genre classification: A semi-supervised approach S Poria, A Gelbukh, A Hussain, S Bandyopadhyay, N Howard Mexican Conference on Pattern Recognition, 254-263, 2013 | 42 | 2013 |
| Computational intelligence for big social data analysis [guest editorial] E Cambria, N Howard, Y Xia, TS Chua IEEE Computational Intelligence Magazine 11 (3), 8-9, 2016 | 33 | 2016 |
| Iodine 131 ablation therapy for a patient on maintenance haemodialysis N Howard, M Glasser The British journal of radiology 54 (639), 259-259, 1981 | 32 | 1981 |
| Automatic detection of acromegaly from facial photographs using machine learning methods X Kong, S Gong, L Su, N Howard, Y Kong EBioMedicine 27, 94-102, 2018 | 28 | 2018 |
| Subliminal priming—state of the art and future perspectives M Elgendi, P Kumar, S Barbic, N Howard, D Abbott, A Cichocki Behavioral Sciences 8 (6), 54, 2018 | 27 | 2018 |
| Why “dark thoughts” aren't really dark: A novel algorithm for metaphor identification D Assaf, Y Neuman, Y Cohen, S Argamon, N Howard, M Last, O Frieder, ... 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms …, 2013 | 26 | 2013 |
| System, method, and applications of using the fundamental code unit and brain language N Howard US Patent 9,399,144, 2016 | 25 | 2016 |
