用于少镜头异常检测的原型学习引导式情境感知分割网络

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 : 2024-10-01 DOI:10.1109/tnnls.2024.3463495

Yuxin Jiang, Yunkang Cao, Weiming Shen

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Prototypical Learning Guided Context-Aware Segmentation Network for Few-Shot Anomaly Detection

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来源期刊

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

Unsupervised Hyperspectral and Multispectral Image Blind Fusion Based on Deep Tucker Decomposition Network With Spatial-Spectral Manifold Learning. Anchor Space Optimal Transport as a Fast Solution to Multiple Optimal Transport Problems. Few-Shot Anomaly Detection via Category-Agnostic Registration Learning. Orthogonal Capsule Networks With Positional Information Preservation and Lightweight Feature Learning. Prototypical Learning Guided Context-Aware Segmentation Network for Few-Shot Anomaly Detection