{"title":"Cross-modal learning with multi-modal model for video action recognition based on adaptive weight training","authors":"Qingguo Zhou, Yufeng Hou, Rui Zhou, Yan Li, JinQiang Wang, Zhen Wu, Hung-Wei Li, Tien-Hsiung Weng","doi":"10.1080/09540091.2024.2325474","DOIUrl":null,"url":null,"abstract":"The canonical video action recognition methods usually label categories with numbers or one-hot vectors and train neural networks to classify a fixed set of predefined categories, thereby constrain...","PeriodicalId":50629,"journal":{"name":"Connection Science","volume":"15 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Connection Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09540091.2024.2325474","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The canonical video action recognition methods usually label categories with numbers or one-hot vectors and train neural networks to classify a fixed set of predefined categories, thereby constrain...
期刊介绍：
Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing.
A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.
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