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Titlebook: Neural Information Processing; 29th International C Mohammad Tanveer,Sonali Agarwal,Adam Jatowt Conference proceedings 2023 The Editor(s) (

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发表于 2025-3-21 18:58:26 | 显示全部楼层 |阅读模式
书目名称Neural Information Processing
副标题29th International C
编辑Mohammad Tanveer,Sonali Agarwal,Adam Jatowt
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Neural Information Processing; 29th International C Mohammad Tanveer,Sonali Agarwal,Adam Jatowt Conference proceedings 2023 The Editor(s) (
描述The three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022..The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications..The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements..
出版日期Conference proceedings 2023
关键词pattern recognition; image processing; signal processing; deep learning; neural networks; computing metho
版次1
doihttps://doi.org/10.1007/978-3-031-30105-6
isbn_softcover978-3-031-30104-9
isbn_ebook978-3-031-30105-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
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 22:22:49 | 显示全部楼层
Patch Mix Augmentation with Dual Encoders for Meta-Learningsing and style mix from AdaIn. Furthermore, we use both ResNet and ViT as our feature encoder. Combining with the idea of contrastive learning, we train our ViT in an unsupervised way. Experimental results show that we achieve a decent performance improvement.
发表于 2025-3-22 02:31:39 | 显示全部楼层
Saccade Direction Information Channelformation of the channel, is higher than in diagonal displacements. By comparing the results to our previous spatial gaze channel between Areas of Interest (AOIs) we constate that the spatial channel discriminates better between the observed images, while the direction channel discriminates better b
发表于 2025-3-22 05:34:52 | 显示全部楼层
Shared-Attribute Multi-Graph Clustering with Global Self-Attention layers in different graphs. 3) A novel self-supervised weighting strategy is proposed to de-emphasize unimportant graphs. Our experiments on four benchmark datasets show the superiority of SAMGC over 14 SOTA methods. The source code is available at ..
发表于 2025-3-22 11:17:38 | 显示全部楼层
Mutual Diverse-Label Adversarial Training method called . (MDLAT). Experiments on CIFAR-10 and CIFAR-100 indicate that our method is effective in improving model robustness under different settings, and our method achieves state-of-the-art (SOTA) robustness under . attack.
发表于 2025-3-22 13:50:19 | 显示全部楼层
Filter Pruning via Similarity Clustering for Deep Convolutional Neural Networksarameters on GoogLeNet, and the accuracy is even 0.09. higher than the baseline model. Moreover, on ImageNet, FPSC reduces more than 43.1. FLOPs and 42.2. parameters, the accuracy only dropped 0.66. on ResNet-50.
发表于 2025-3-22 18:15:55 | 显示全部楼层
FPD: Feature Pyramid Knowledge Distillationhese issues, our study aims to narrow the gap in feature representation between teacher and student and obtain more feature representation from images in limited datasets to achieve better performance. In addition, the superiority of our method is all validated on a generalized dataset (CIFAR-100) a
发表于 2025-3-23 00:43:14 | 显示全部楼层
Self-Reinforcing Feedback Domain Adaptation Channel feedback mechanism, SRFC skillfully integrates multi-level information in a robust way in the process of domain adaptation, and actively enhances the availability and comprehensive value of features in domain adaptation with manageable continuous feedback. Experiments on benchmark datasets verify t
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d) class libraries, application frameworks, and design patterns. Software components provide a vehicle for planned and systematic reuse. The software community does not yet agree on what a software component is exactly. Nowadays, the term component is used as a synonym for object most of the time, but it also978-3-642-08299-3978-3-662-03345-6
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