Appearance Meets Geometry: Deep Learning for Semantic Segmentation of Archaeological Fortification Masonry

# 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

Two-stage deep learning for segmenting in concrete X-ray CT images

Youxi Wang

Code and data deposit for a two-stage ViT–UNet concrete CT segmentation study. Includes training/evaluation scripts, reproducibility logs (split seed 42), and 151 public test patches (images + masks). Train/val data, 0401 manual labels, and weights excluded. CC BY-NC 4.0.

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

A High-Performance Scalable Architecture for Cloud-Based Deep Learning and Data-Intensive Applications

Grace Dooshima GBOR, Emmanuel Ogala, Donald Douglas Atsa’am, Iorshashe Agaji

Abstract The rapid growth of big data and the increasing complexity of deep learning applications have created significant challenges for traditional data processing infrastructures, particularly in terms of scalability, performance, and resource efficiency. This study presents a…Read more