16 citations · 16 across the 3 of their papers we have counts for
5 papers
LoOp: Looking for Optimal Hard Negative Embeddings for Deep Metric Learning
Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya +2
Deep metric learning has been effectively used to learn distance metrics for different visual tasks like image retrieval, clustering, etc. In order to aid the training process, exi…
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov, Radu Timofte, Zhilu Zhang +36
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…
Co-VeGAN: Complex-Valued Generative Adversarial Network for Compressive Sensing MR Image Reconstruction
Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya +1
Compressive sensing (CS) is widely used to reduce the acquisition time of magnetic resonance imaging (MRI). Although state-of-the-art deep learning based methods have been able to…
Efficient Implementation of LMS Adaptive Filter based FECG Extraction on an FPGA
Bhavya Vasudeva, Puneesh Deora, Pyari Mohan Pradhan +1
In this paper, the field programmable gate array (FPGA) implementation of a fetal heart rate (FHR) monitoring system is presented. The system comprises of a preprocessing unit to r…
Structure Preserving Compressive Sensing MRI Reconstruction using Generative Adversarial Networks
Puneesh Deora, Bhavya Vasudeva, Saumik Bhattacharya +1
Compressive sensing magnetic resonance imaging (CS-MRI) accelerates the acquisition of MR images by breaking the Nyquist sampling limit. In this work, a novel generative adversaria…