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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23Cited by 0

Data from: Automated Ethogram Elaboration: A Cross-species Deep-learning Model Deployed On-board Enables Acceleration-triggered Capture of Diverse Behavioural Video

Tsuneari Kuroiwa

This record contains field-deployment datasets for two seabird species, streaked shearwaters and black-tailed gulls, used in the paper “Automated Ethogram Elaboration: A Cross-species Deep-learning Model Deployed On-board Enables Acceleration-triggered Capture of Diverse Behavioural Video” (Kuroiwa et al., in review). See README.md for the full column schema, file structure, and label definitions.

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23

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…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-08-01

Deep Learning Enables Transferable Rheological Parameters for Landslide Runout Prediction

Yunxu Xie

This dataset contains numerical simulation results and deep-learning–based predictions used to investigate transferable rheological parameters for landslide runout modeling. The data were generated using a physics-based shallow water equation (SWE) framework coupled with a deep n…

Also available via: European Organization for Nuclear Research

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23

Dataset for "Deep learning models for estimating volume and Lorey's height across Nordic countries using optical and SAR satellite images" article

Zsófia Koma, Oleg Antropov, Jukka Miettinen, Johannes Breidenbach

This repository contains the data products and code required to reproduce the results presented in the article "Deep Learning Models for Estimating Volume and Lorey's Height Across Nordic Countries Using Optical and SAR Satellite Images". The study investigates the use of U-Net d…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-25

# 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…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-08-09

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…

Also available via: European Organization for Nuclear Research

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

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…

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