Deep Learning Enables Transferable Rheological Parameters for Landslide Runout Prediction

# 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

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

ML Precipitation Prediction: Hybrid Deep Learning for Spatiotemporal Forecasting in Mountainous Areas

Manuel Ricardo Perez Reyes

A hybrid deep learning framework for monthly precipitation prediction in mountainous areas of Boyacá, Colombia. Combines Graph Neural Networks (GNN) with temporal attention mechanisms and ConvLSTM architectures for accurate spatiotemporal forecasting. This implementation includes…Read more

Neuro-Oncology Benchmark: The Resource-Interpretability Tradeoff in Radiomics and Multiclass Brain Tumor Classification Based on Deep Transfer Learning vs Handcrafted Radiomics.

Othmane Bakkas, Drissia Ennagoura, Nasreen Badruddin, Abdelali Zbakh, Mohamed El Mahjouby, Badre Bossoufi, et al.

The automatic multiclass brain tumor classification using MRI images plays an important role in a non-invasive clinical setting. However, the choice of a model demands the trade-off between accuracy, complexity, and interpretability of the classifier. In this study, we have estab…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

PULSE-72: Single-Cell Pulse and Drive-Cycle Dataset for ARGUS (Mixed-Training Deep Learning for Equivalent Circuit Parameter Identification in Lithium-Ion Batteries)

A. P. Druzhinin

The dataset was acquired from tests of a commercial LG INR18650 MJ1 lithium-ion cell (nominal capacity 3500 mAh).For equivalent-circuit parameterization, we used voltage responses to rectangular galvanostatic current pulses with durations from 9 to 144 s and amplitudes of approxi…Read more