Journal Article

• Multi-resolution approach to human activity recognition in video sequence based on combination of complex wavelet transform Local Binary Pattern and Zernike moment Multimedia Tools and Applications, 1174: Futuristic Trends and Innovations in Multimedia Systems Using Big Data, IoT and Cloud Technologies (FTIMS) 04 Feb. 2022. doi:10.1007/s11042-021-11828-6.
• Assessing Mobile Usage Physical Activity and Sleep Through Smartphone Sensing: A Digital Phenotype Study SN Computer Science, Springer vol. 03, Issue 5, article no.: 331 13 Jun. 2022 doi: 10.1007/s42979-022-01221-x.
• Vijeta Khare "Tchebichef Transform Domain-Based Deep Learning Architecture for Image Super-Resolution," IEEE Transactions on Neural Networks and Learning Systems, 13 Jul. 2022, pp. 1-12, IEEE, doi: 10.1109/TNNLS.2022.3188452. [Early Access]
• The yin–yang codec for archival DNA storage News & Views, Nature Computational Science, Nature 25 Apr. 2022. doi:10.1038/s43588-022-00235-y.
• A novel approach for design of beam steerable aperiodic planar array antenna with reduced number of elements  Journal of Electromagnetic Waves and Applications, Taylor & Francis Publications1 Oct. 2021. doi: 10.1080/09205071.2021.1983474
• Broadband microwave absorber using pixelated FSS embedded in CISR sheets in frequency range of 3.95 to 8.2?GHz  Journal of Electromagnetic Waves and Applications, Taylor & Francis Publications, vol. 35, Issue 17 pp. 2349-2367 6 Jul 2021. doi: 10.1080/09205071.2021.1947899
• Non-intrusive quality assessment of noise-suppressed speech using unsupervised deep features  Speech Communication, vol. 130 pp. 27-44 Jun. 2021. doi: 10.1016/j.specom.2021.03.004
• Weather impact on macroscopic traffic stream variables prediction using recurrent learning approach Journal of Intelligent Transportation Systems , Taylor & Francis Publications 24 Oct. 2021. doi: 10.1080/15472450.2021.1983809
• The balanced connected subgraph problem Discrete Applied Mathematics, Elsevier B.V. 2021 doi: 10.1016/j.dam.2020.12.030.
• Residual Neural Network precisely quantifies dysarthria severity-level based on short-duration speech segments  Neural Networks, Elsevier vol. 139 pp. 105-117 Jul. 2021. doi:10.1016/j.neunet.2021.02.008.