Explainable AI in human motion: A comprehensive approach to analysis, modeling, and generation-Reference-Cited by-同舟云学术

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Explainable AI in human motion: A comprehensive approach to analysis, modeling, and generation

Published:2024-07 Issue: Volume:151 Page:110418
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Olivas-Padilla Brenda Elizabeth^ORCID,Manitsaris Sotiris^ORCID,Glushkova Alina^ORCID

Funder

Horizon 2020

Publisher

Elsevier BV

Reference40 articles.

1. Spatiotemporal co-attention recurrent neural networks for human-skeleton motion prediction;Shu;IEEE Trans. Pattern Anal. Mach. Intell.,2022

2. Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-AI;Auletta;Sci. Rep.,2023

3. A novel explainable neural network for Alzheimer’s disease diagnosis;Yu;Pattern Recognit.,2022

4. AIFit: Automatic 3D human-interpretable feedback models for fitness training;Fieraru,2021

5. Kinematic coordinations capture learning during human–exoskeleton interaction;Ghonasgi;Sci. Rep.,2023

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A behavioral conditional diffusion probabilistic model for human motion modeling in multi-action mixed human-robot collaboration;Advanced Engineering Informatics;2024-10

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