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

ML Precipitation Prediction Framework

Manuel Ricardo Pérez Reyes, Marco Javier Suárez Barón, Oscar García-Cabrejo, Octavio Castillo-Reyes

Open-source framework for monthly precipitation prediction in mountainous areas using hybrid deep learning. The framework provides reference implementations for eight model families and a uniform training, evaluation, and benchmarking pipeline: ConvLSTM family — baseline, bidirec…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

# 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

Multi-Modal Deepfake Detection System Using Hybrid Deep Learning on Visual and Audio Features

Nandana K Gowda, P Hemavathi

Abstract: Deepfake technology, driven by generative models such as GANs and diffusion architectures, has enabled the creation of highly realistic manipulated media capable of deceiving both visual and auditory perception. Such forgeries pose significant risks to identity verifica…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

M3SpaDE: A Multi-Modal Deep Learning Framework for Predicting Spatially Resolved Drug Responses

Zihao Zhang, Xinyu Cui, Zhengke Lian, Xiufeng Pang, Ye, Youqiong, Jiang, Cizhong

M3SpaDE (Multi-Modal Model for predicting Spatial Drug Efficacy) is a versatile computational framework designed for predicting drug sensitivity in spatial transcriptomics data. It is resolution-agnostic, capable of processing data ranging from single-cell to spot-level resolutio…Read more

Also available via: European Organization for Nuclear Research