Zobrazeno 1 - 10
of 2 010
pro vyhledávání: '"A. Dasmahapatra"'
Alzheimer's disease (AD) is a neurodegenerative disorder; it is the most common form of de-mentia and the fifth leading cause of death globally. Aggregation and deposition of neurotoxic A-beta fibrils in the neural tissues of the brain is a key hallm
Externí odkaz:
http://arxiv.org/abs/2406.04852
In the attempt to explain possible data anomalies from collider experiments in terms of New Physics (NP) models, computationally expensive scans over their parameter spaces are typically required in order to match theoretical predictions to experimen
Externí odkaz:
http://arxiv.org/abs/2404.18653
Autor:
Diaz, Mauricio A., Cerro, Giorgio, Chaplais, Jacan, Dasmahapatra, Srinandan, Moretti, Stefano
Machine learning has played a pivotal role in advancing physics, with deep learning notably contributing to solving complex classification problems such as jet tagging in the field of jet physics. In this experiment, we aim to harness the full potent
Externí odkaz:
http://arxiv.org/abs/2311.14654
Weight-sharing quantization has emerged as a technique to reduce energy expenditure during inference in large neural networks by constraining their weights to a limited set of values. However, existing methods for weight-sharing quantization often ma
Externí odkaz:
http://arxiv.org/abs/2309.13575
Achieving accurate material segmentation for 3-channel RGB images is challenging due to the considerable variation in a material's appearance. Hyperspectral images, which are sets of spectral measurements sampled at multiple wavelengths, theoreticall
Externí odkaz:
http://arxiv.org/abs/2307.11466
DBAT: Dynamic Backward Attention Transformer for Material Segmentation with Cross-Resolution Patches
The objective of dense material segmentation is to identify the material categories for every image pixel. Recent studies adopt image patches to extract material features. Although the trained networks can improve the segmentation performance, their
Externí odkaz:
http://arxiv.org/abs/2305.03919
Incorporating either rotation equivariance or scale equivariance into CNNs has proved to be effective in improving models' generalization performance. However, jointly integrating rotation and scale equivariance into CNNs has not been widely explored
Externí odkaz:
http://arxiv.org/abs/2304.04600
Digital histopathology slides are scanned and viewed under different magnifications and stored as images at different resolutions. Convolutional Neural Networks (CNNs) trained on such images at a given scale fail to generalise to those at different s
Externí odkaz:
http://arxiv.org/abs/2304.04595
The UNet model consists of fully convolutional network (FCN) layers arranged as contracting encoder and upsampling decoder maps. Nested arrangements of these encoder and decoder maps give rise to extensions of the UNet model, such as UNete and UNet++
Externí odkaz:
http://arxiv.org/abs/2304.04567
Autor:
Chakraborty, Amit, Dasmahapatra, Srinandan, Day-Hall, Henry, Ford, Billy, Jain, Shubhani, Moretti, Stefano
We compare different jet-clustering algorithms in establishing fully hadronic final states stemming from the chain decay of a heavy Higgs state into a pair of the 125 GeV Higgs boson that decays into bottom-antibottom quark pairs. Such 4$b$ events ty
Externí odkaz:
http://arxiv.org/abs/2303.05189