Bindu Verma. "A two stream convolutional neural network with bi-directional GRU model to classify dynamic hand gesture." Journal of Visual Communication and Image Representation (2022): 103554.[SCIE: 2.8]
Bindu Verma, and Ayesha Choudhary. “Framework for dynamic hand gesture recognition using Grassmann manifold for intelligent vehicles.” Journal of IET Intelligent Transport Systems Vol.12, no.7 pp. 721-729, 2018. DOI: 10.1049/IET-ITS.2017.0331 [SCIE: 2.7]
Bindu Verma, Ayesha Choudhary, Grassmann manifold based dynamic hand gesture recognition using depth data. Multimed Tools Appl 79, 2213–2237 (2020). https://doi.org/10.1007/s11042-019-08266-w [SCIE 2.7]
Bindu Verma, Ayesha Choudhary, Affective state recognition from hand gestures and facial expressions using Grassmann manifolds. Multimed Tools Appl 80, 14019–14040 (2021). https://doi.org/10.1007/s11042-020-10341-6 [SCIE 2.7]
Bindu Verma, and Ayesha Choudhary. “Unsupervised learning based static hand gesture recognition from RGB-D sensor.” In International Conference on Soft Computing and Pattern Recognition,pp. 304-314. Springer, Cham, 2016.
Bindu Verma, and Ayesha Choudhary. “Deep Learning Based Real-Time Driver Emotion Monitoring.” In IEEE International Conference on Vehicular Electronics and Safety (ICVES), pp.1-6., 2018.
Bindu Verma, and Ayesha Choudhary, “A Framework for Driver Emotion Recognition using Deep Learning and Grassmann Manifolds”, In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 1421-1426, 2018.
Gupta I, Garg N, Aggarwal A, Nepalia N, Verma B. Real-time driver's drowsiness monitoring based on dynamically varying threshold. In2018 Eleventh International Conference on Contemporary Computing (IC3) 2018 Aug 2 (pp. 1-6). IEEE.
Bindu Verma, and Ayesha Choudhary, Dynamic Hand Gesture Recognition using Convolutional Neural Network with RGB-D Fusion. InProceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing 2018 Dec 18 (pp. 1-8).