SpikeSegNet-a deep learning approach utilizing encoder-decoder network with hourglass for spike segmentation and counting in wheat plant from visual imaging T Misra, A Arora, S Marwaha, V Chinnusamy, AR Rao, R Jain, RN Sahoo, ... Plant methods 16, 1-20, 2020 | 93 | 2020 |
An efficient finger-knuckle-print based recognition system fusing sift and surf matching scores GS Badrinath, A Nigam, P Gupta Information and Communications Security: 13th International Conference …, 2011 | 85 | 2011 |
Multiple texture information fusion for finger-knuckle-print authentication system A Nigam, K Tiwari, P Gupta Neurocomputing 188, 190-205, 2016 | 70 | 2016 |
PVSNet: Palm vein authentication siamese network trained using triplet loss and adaptive hard mining by learning enforced domain specific features D Thapar, G Jaswal, A Nigam, V Kanhangad 2019 IEEE 5th international conference on identity, security, and behavior …, 2019 | 64 | 2019 |
A comprehensive survey and deep learning-based approach for human recognition using ear biometric A Kamboj, R Rani, A Nigam The Visual Computer 38 (7), 2383-2416, 2022 | 60 | 2022 |
Designing an accurate hand biometric based authentication system fusing finger knuckleprint and palmprint A Nigam, P Gupta Neurocomputing 151, 1120-1132, 2015 | 57 | 2015 |
Iris segmentation using improved hough transform A Bendale, A Nigam, S Prakash, P Gupta Emerging Intelligent Computing Technology and Applications: 8th …, 2012 | 55 | 2012 |
VGR-net: A view invariant gait recognition network D Thapar, A Nigam, D Aggarwal, P Agarwal 2018 IEEE 4th international conference on identity, security, and behavior …, 2018 | 51 | 2018 |
Deep metric learning for bioacoustic classification: Overcoming training data scarcity using dynamic triplet loss A Thakur, D Thapar, P Rajan, A Nigam The Journal of the Acoustical Society of America 146 (1), 534-547, 2019 | 48 | 2019 |
PixISegNet: pixel‐level iris segmentation network using convolutional encoder–decoder with stacked hourglass bottleneck RR Jha, G Jaswal, D Gupta, S Saini, A Nigam IET biometrics 9 (1), 11-24, 2020 | 43 | 2020 |
DeepKnuckle: revealing the human identity G Jaswal, A Nigam, R Nath Multimedia Tools and Applications 76 (18), 18955-18984, 2017 | 42 | 2017 |
Single-sensor hand-vein multimodal biometric recognition using multiscale deep pyramidal approach S Bhilare, G Jaswal, V Kanhangad, A Nigam Machine Vision and Applications 29 (8), 1269-1286, 2018 | 38 | 2018 |
Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach PK Jain, S Gupta, A Bhavsar, A Nigam, N Sharma Medical & Biological Engineering & Computing 58, 471-482, 2020 | 35 | 2020 |
VStegNET: Video Steganography Network using Spatio-Temporal features and Micro-Bottleneck. A Mishra, S Kumar, A Nigam, S Islam BMVC 274, 2019 | 35 | 2019 |
3D face recognition using kinect R Ajmera, A Nigam, P Gupta Proceedings of the 2014 Indian conference on computer vision graphics and …, 2014 | 34 | 2014 |
Gait metric learning siamese network exploiting dual of spatio-temporal 3D-CNN intra and LSTM based inter gait-cycle-segment features D Thapar, G Jaswal, A Nigam, C Arora Pattern Recognition Letters 125, 646-653, 2019 | 32 | 2019 |
A new distance measure for face recognition system A Nigam, P Gupta 2009 Fifth International Conference on Image and Graphics, 696-701, 2009 | 29 | 2009 |
Finger knuckleprint based recognition system using feature tracking A Nigam, P Gupta Biometric Recognition: 6th Chinese Conference, CCBR 2011, Beijing, China …, 2011 | 27 | 2011 |
Iris recognition using consistent corner optical flow A Nigam, P Gupta Asian Conference on Computer Vision, 358-369, 2012 | 26 | 2012 |
Hierarchical X-ray report generation via pathology tags and multi head attention P Srinivasan, D Thapar, A Bhavsar, A Nigam Proceedings of the Asian Conference on Computer Vision, 2020 | 25 | 2020 |