用于放宽分布外样本过度置信度的平缓倾斜和扩展分类保证金

IF 10.2 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE transactions on neural networks and learning systems Pub Date : 2024-11-20 DOI:10.1109/tnnls.2024.3496473
Taewook Kim, Jong-Seok Lee
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Gently Sloped and Extended Classification Margin for Overconfidence Relaxation of Out-of-Distribution Samples
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来源期刊
IEEE transactions on neural networks and learning systems
IEEE transactions on neural networks and learning systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
CiteScore
23.80
自引率
9.60%
发文量
2102
审稿时长
3-8 weeks
期刊介绍: The focus of IEEE Transactions on Neural Networks and Learning Systems is to present scholarly articles discussing the theory, design, and applications of neural networks as well as other learning systems. The journal primarily highlights technical and scientific research in this domain.
期刊最新文献
Adaptive Graph Convolutional Network for Unsupervised Generalizable Tabular Representation Learning Gently Sloped and Extended Classification Margin for Overconfidence Relaxation of Out-of-Distribution Samples NNG-Mix: Improving Semi-Supervised Anomaly Detection With Pseudo-Anomaly Generation Alleviate the Impact of Heterogeneity in Network Alignment From Community View Hierarchical Contrastive Learning for Semantic Segmentation
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