116 citations · 329 across the 40 of their papers we have counts for
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EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search
Pedram Bakhtiarifard, Christian Igel, Raghavendra Selvan
Energy consumption from the selection, training, and deployment of deep learning models has seen a significant uptick recently. This work aims to facilitate the design of energy-ef…
Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation
Nicklas Boserup, Raghavendra Selvan
Learning discriminative representations of unlabelled data is a challenging task. Contrastive self-supervised learning provides a framework to learn meaningful representations usin…
Interpreting Latent Spaces of Generative Models for Medical Images using Unsupervised Methods
Julian Schön, Raghavendra Selvan, Jens Petersen
Generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) play an increasingly important role in medical image analysis. The latent space…
Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis
Raghavendra Selvan, Nikhil Bhagwat, Lasse F. Wolff Anthony +2
The increasing energy consumption and carbon footprint of deep learning (DL) due to growing compute requirements has become a cause of concern. In this work, we focus on the carbon…