8 citations · 17 across the 6 of their papers we have counts for
6 papers
FPBench: A Comprehensive Benchmark of Multimodal Large Language Models for Fingerprint Analysis
Ekta Gavas, Sudipta Banerjee, Chinmay Hegde +1
Multimodal LLMs (MLLMs) are capable of performing complex data analysis, visual question answering, generation, and reasoning tasks. However, their ability to analyze biometric dat…
DiffClean: Diffusion-based Makeup Removal for Accurate Age Estimation
Ekta Gavas, Sudipta Banerjee, Chinmay Hegde +1
Accurate age verification can protect underage users from unauthorized access to online platforms and e-commerce sites that provide age-restricted services. However, accurate age e…
Enhancement-Driven Pretraining for Robust Fingerprint Representation Learning
Ekta Gavas, Kaustubh Olpadkar, Anoop Namboodiri
Fingerprint recognition stands as a pivotal component of biometric technology, with diverse applications from identity verification to advanced search tools. In this paper, we prop…
Finger-UNet: A U-Net based Multi-Task Architecture for Deep Fingerprint Enhancement
Ekta Gavas, Anoop Namboodiri
For decades, fingerprint recognition has been prevalent for security, forensics, and other biometric applications. However, the availability of good-quality fingerprints is challen…
Center Loss Regularization for Continual Learning
Kaustubh Olpadkar, Ekta Gavas
The ability to learn different tasks sequentially is essential to the development of artificial intelligence. In general, neural networks lack this capability, the major obstacle b…
Deep CNNs for Peripheral Blood Cell Classification
Ekta Gavas, Kaustubh Olpadkar
The application of machine learning techniques to the medical domain is especially challenging due to the required level of precision and the incurrence of huge risks of minute err…