8 citations · 8 across the 2 of their papers we have counts for
5 papers
PoshakNet: Framework for matching dresses from real-life photos using GAN and Siamese Network
Abhigyan Khaund, Daksh Thapar, Aditya Nigam
Online garment shopping has gained many customers in recent years. Describing a dress using keywords does not always yield the proper results, which in turn leads to dissatisfactio…
FKIMNet: A Finger Dorsal Image Matching Network Comparing Component (Major, Minor and Nail) Matching with Holistic (Finger Dorsal) Matching
Daksh Thapar, Gaurav Jaswal, Aditya Nigam
Current finger knuckle image recognition systems, often require users to place fingers' major or minor joints flatly towards the capturing sensor. To extend these systems for user…
Multiscale CNN based Deep Metric Learning for Bioacoustic Classification: Overcoming Training Data Scarcity Using Dynamic Triplet Loss
Anshul Thakur, Daksh Thapar, Padmanabhan Rajan +1
This paper proposes multiscale convolutional neural network (CNN)-based deep metric learning for bioacoustic classification, under low training data conditions. The proposed CNN is…
PVSNet: Palm Vein Authentication Siamese Network Trained using Triplet Loss and Adaptive Hard Mining by Learning Enforced Domain Specific Features
Daksh Thapar, Gaurav Jaswal, Aditya Nigam +1
Designing an end-to-end deep learning network to match the biometric features with limited training samples is an extremely challenging task. To address this problem, we propose a…
BrainSegNet : A Segmentation Network for Human Brain Fiber Tractography Data into Anatomically Meaningful Clusters
Tushar Gupta, Shreyas Malakarjun Patil, Mukkaram Tailor +2
The segregation of brain fiber tractography data into distinct and anatomically meaningful clusters can help to comprehend the complex brain structure and early investigation and m…