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Titlebook: Deep Learning Theory and Applications; 4th International Co Donatello Conte,Ana Fred,Carlo Sansone Conference proceedings 2023 The Editor(s

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发表于 2025-3-21 19:27:56 | 显示全部楼层 |阅读模式
书目名称Deep Learning Theory and Applications
副标题4th International Co
编辑Donatello Conte,Ana Fred,Carlo Sansone
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Deep Learning Theory and Applications; 4th International Co Donatello Conte,Ana Fred,Carlo Sansone Conference proceedings 2023 The Editor(s
描述This book consitiutes the refereed proceedings of the 4th International Conference on Deep Learning Theory and Applications, DeLTA 2023, held in Rome, Italy from 13 to 14 July 2023..The 9 full papers and 22 short papers presented were thoroughly reviewed and selected from the 42 qualified submissions. The scope of the conference includes such topics as models and algorithms; machine learning; big data analytics; computer vision applications; and natural language understanding..
出版日期Conference proceedings 2023
关键词artificial intelligence; computer security; data security; distributed systems; parallel processing syst
版次1
doihttps://doi.org/10.1007/978-3-031-39059-3
isbn_softcover978-3-031-39058-6
isbn_ebook978-3-031-39059-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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发表于 2025-3-21 20:18:16 | 显示全部楼层
,A Study of Neural Collapse for Text Classification,this additional cluster represents an additional topic within the dataset, challenging the initial assumption of four distinct classes in AG News. This significant discovery suggests a promising research direction, where NC can serve as a tool for cluster discovery in semi-supervised learning scenarios.
发表于 2025-3-22 03:23:26 | 显示全部楼层
发表于 2025-3-22 08:15:05 | 显示全部楼层
Zhongwei Gu,Youxiang Cui,Haibo Tang,Xiao Liue make use of convolutional neural networks (CNN) and various data-augmentation techniques. We showcase the results of this approach on the challenging . dataset, with the task of classifying between different primate species sounds, and report significantly higher Accuracy and UAR scores in contrast to comparatively equipped model baselines.
发表于 2025-3-22 11:26:30 | 显示全部楼层
发表于 2025-3-22 12:59:29 | 显示全部楼层
Yun Liang,Junyi Mo,Yi Lu,Xing Yuan. Finally, we present an ablation study to validate our approach. We discovered that data2vec appears to be the best option if time and lightweightness are critical factors. On the other hand, wav2vec2phoneme is the most appropriate choice if overall performance is the primary criterion.
发表于 2025-3-22 20:27:28 | 显示全部楼层
Improving Primate Sounds Classification Using Binary Presorting for Deep Learning,e make use of convolutional neural networks (CNN) and various data-augmentation techniques. We showcase the results of this approach on the challenging . dataset, with the task of classifying between different primate species sounds, and report significantly higher Accuracy and UAR scores in contrast to comparatively equipped model baselines.
发表于 2025-3-23 00:59:38 | 显示全部楼层
An Automated Dual-Module Pipeline for Stock Prediction: Integrating N-Perception Period Power Stratlenges, we propose an automated pipeline consisting of two modules: an N-Perception period power strategy for identifying potential stocks and a sentiment analysis module using NLP techniques to capture market sentiment. By incorporating these methodologies, we aim to enhance stock prediction accuracy and provide valuable insights for investors.
发表于 2025-3-23 02:40:53 | 显示全部楼层
,Phoneme-Based Multi-task Assessment of Affective Vocal Bursts,. Finally, we present an ablation study to validate our approach. We discovered that data2vec appears to be the best option if time and lightweightness are critical factors. On the other hand, wav2vec2phoneme is the most appropriate choice if overall performance is the primary criterion.
发表于 2025-3-23 06:23:49 | 显示全部楼层
1865-0929 submissions. The scope of the conference includes such topics as models and algorithms; machine learning; big data analytics; computer vision applications; and natural language understanding..978-3-031-39058-6978-3-031-39059-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
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