Nuclear & Particle Physics — Deep Learning Tutor

# Artificial Intelligence-Enabled Quantification of Cube and Goss Textures in Polycrystalline Materials: A Comprehensive Review of Machine Learning, Deep Learning, and EBSD-Based Characterization Approaches

Sudhakar Geruganti

## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…Read more

Evaluation of the Implementation of the Deep Learning Approach in Learning in the Subject of PJOK in Public Junior High Schools in Godean District

Andi Raafa Firmansyach, Ngatman

This study aims to evaluate the implementation of the deep learning approach in Physical Education, Sports, and Health (PJOK) learning in public junior high schools in Godean District, based on the Countenance Stake Evaluation Model, which includes antecedents, transactions, and…Read more

A Systematic Review of Machine Learning, Deep Learning, and Explainable AI Approaches for Cardiac Disease Prediction

Sunanda Budihal, Sheetalrani Kawale, Abhishek Angadi

The cardiovascular (Cardiac) disease (CVD) is another factor that causes death among the global population most, and this is the reason why there is a high necessity to implement proper, effective, and interpretive diagnostic systems. The usage of machine learning (ML), deep lear…Read more

Also available via: European Organization for Nuclear Research

Client Recognition Using Text-Dependent Voice Biometrics: A Machine Learning and Deep Learning Approach

Annual Methodological Archive Research Review

Low Dose and High Contrast Biomedical Imaging Using SelfSupervised Deep Learning

Xiao Fan Ding, Xiaoman Duan, Ning Zhu

Self-supervised deep learning has emerged as a powerful method for image enhancement when a priori ground-truth references are not available. Stemming from Noise2Noise , it was shown that a convolutional neural network (CNN) can be trained from a noisy input and target pair of th…Read more

Also available via: European Organization for Nuclear Research

Replication package for: "Taming the Curse of Dimensionality: Quantitative Economics with Deep Learning"

Jesus Fernandez-Villaverde, Galo Nuño, Jesse Perla

Replication package for "Taming the Curse of Dimensionality: Quantitative Economics with Deep Learning." The paper “Taming the Curse of Dimensionality: Quantitative Economics with Deep Learning” is purely computational: it uses no external data, and all numerical results are prod…Read more