| Speech Emotion Recognition Using Spectrogram & Phoneme Embedding. P Yenigalla, A Kumar, S Tripathi, C Singh, S Kar, J Vepa Interspeech 2018, 3688-3692, 2018 | 211 | 2018 |
| Deceptive reviews detection using deep learning techniques N Jain, A Kumar, S Singh, C Singh, S Tripathi Natural Language Processing and Information Systems: 24th International …, 2019 | 37 | 2019 |
| Focal loss based residual convolutional neural network for speech emotion recognition S Tripathi, A Kumar, A Ramesh, C Singh, P Yenigalla arXiv preprint arXiv:1906.05682, 2019 | 19 | 2019 |
| Learning discriminative features using center loss and reconstruction as regularizer for speech emotion recognition S Tripathi, A Ramesh, A Kumar, C Singh, P Yenigalla Workshop on Artificial Intelligence in Affective Computing, 44-53, 2020 | 16 | 2020 |
| Addressing unseen word problem in text classification P Yenigalla, S Kar, C Singh, A Nagar, G Mathur Natural Language Processing and Information Systems: 23rd International …, 2018 | 15 | 2018 |
| Bidirectional transformer based multi-task learning for natural language understanding S Tripathi, C Singh, A Kumar, C Pandey, N Jain Natural Language Processing and Information Systems: 24th International …, 2019 | 10 | 2019 |
| Exploiting sift descriptor for rotation invariant convolutional neural network A Kumar, N Jain, C Singh, S Tripathi 2018 15th IEEE India Council International Conference (INDICON), 1-5, 2018 | 9 | 2018 |
| From fully supervised to zero shot settings for twitter hashtag recommendation A Kumar, N Jain, S Tripathi, C Singh arXiv preprint arXiv:1906.04914, 2019 | 7 | 2019 |
| Mtcnet: Multi-task learning paradigm for crowd count estimation A Kumar, N Jain, S Tripathi, C Singh, K Krishna arXiv preprint arXiv:1908.08652, 2019 | 2 | 2019 |
Abhay KumarWalmart Labs, University of Wisconsin-Madison, Samsung Research, IIT Kanpur在 wisc.edu 的电子邮件经过验证
