* denotes equal contribution.                                For latest: Google Scholar

2021
  1. [J8] Buckchash, H., & Raman, B., 2021. GraSP: Local Grassmannian Spatio-Temporal Patterns for Unsupervised Pose Sequence Recognition. In ACM Transactions on Multimedia Computing, Communications, and Applications. [in press]
  2. [J7] Arora*, R., Bansal*, V., Buckchash*, H., et al., 2021. AI-Based Diagnosis of COVID-19 Patients Using X-Ray Scans With Stochastic Ensemble of CNNs. In Physical and Engineering Sciences in Medicine. [in press]
  3. [J6] Bansal*, V., Buckchash*, H., & Raman, B., 2022. Computational intelligence enabled student performance estimation in the age of COVID-19. In SN Computer Science, 3(41). [link]
  4. [J5] Buckchash, H., & Raman, B., 2021. Towards Zero Shot Learning of Geometry of Motion Streams and Its Application to Anomaly Recognition. In Expert Systems with Applications, 177(1), pp. 114916. [link]
  5. [J4] Bansal*, V., Buckchash*, H., & Raman, B., 2021. Discriminative Auto-Encoding for Classification and Representation Learning Problems. In IEEE Signal Processing Letters, 28(1), pp. 987-991. [link]
2020
  1. [C7] Buckchash, H., & Raman, B., 2020. DuTriNet: Dual-Stream Triplet Siamese Network for Self-Supervised Action Recognition by Modeling Temporal Correlations. In 32nd IEEE International Conference on Tools with Artificial Intelligence (ICTAI),  pp. 488-495. [link]
  2. [C6] Buckchash, H., & Raman, B., 2020. Human Motion Generation by Stochastic Conditioning of Deep Recurrent Networks on Pose Manifolds. In 27th IEEE International Conference on Image Processing (ICIP),  pp. 2406-2410. [link]
  3. [C5] Kundu*, J. N., Buckchash*, H., Mandikal, P., Venkatesh, R. M., Jamkhandi, A., & Babu, R. V., 2020. Cross-conditioned Recurrent Networks for Long-term Synthesis of Inter-person Human Motion Interactions. In The IEEE Winter Conference on Applications of Computer Vision (WACV),  pp. 2724-2733. [link]
  4. [J3] Buckchash, H., & Raman, B., 2020. Variational Conditioning of Deep Recurrent Networks for Modeling Complex Motion Dynamics. In IEEE Access, 8(1), pp. 67822-67834. [link]
  5. [P1] Kumar, R., Arora, R., Bansal, V., Sahayasheela, V. J., Buckchash, H., et al., 2020. Accurate Prediction of COVID-19 Using Chest X-Ray Images Through Deep Feature Learning Model With SMOTE and Machine Learning Classifiers. [link]
2019
  1. [C4] Buckchash, H., & Raman, B., 2019. Sustained Self-Supervised Pretraining for Temporal Order Verification. In 8th International Conference on Pattern Recognition & Machine Intelligence (PReMI), pp. 140-149. Springer, Cham. [link]
  2. [J2] Tanwar, V. K., Buckchash, H., Raman, B., & Bhargava, R., 2018. Dense Motion Analysis of German Finger Spellings. In Multimedia Tools and Applications, 78(8), pp. 9511-9536. [link]
2018
  1. [C3] Pundir, A. S., Buckchash, H., Rajput, A. S., Tanwar, V. K., & Raman, B., 2018. Fire Detection Using Dense Trajectories. In Proceedings of 2nd International Conference on Computer Vision & Image Processing (CVIP), pp. 211-221. Springer, Singapore. [link]
2017
  1. [C2] Kushwaha, P., Buckchash, H., & Raman, B., 2017. Anomaly Based Intrusion Detection Using Filter Based Feature Selection on KDD-CUP 99. In 2017 IEEE Region 10 Conference (TENCON), pp. 839-844. IEEE. [link]
  2. [C1] Buckchash, H., & Raman, B., 2017. A Robust Object Detector: Application to Detection of Visual Knives. In 2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEw), pp. 633-638. IEEE. [link]
2015
  1. [J1] Buckchash, H., & Verma, G. K., 2015. Texture vs. Multiresolution Analysis of Facial Expressions: Application to Emotion Recognition. In International Journal of Applied Pattern Recognition, 2(1), pp. 46-75. [link]

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