Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Luo Haichi"'
Unsupervised anomaly detection methods are at the forefront of industrial anomaly detection efforts and have made notable progress. Previous work primarily used 2D information as input, but multi-modal industrial anomaly detection based on 3D point c
Externí odkaz:
http://arxiv.org/abs/2311.06797
In the anomaly detection field, the scarcity of anomalous samples has directed the current research emphasis towards unsupervised anomaly detection. While these unsupervised anomaly detection methods offer convenience, they also overlook the crucial
Externí odkaz:
http://arxiv.org/abs/2311.06794
Fine-Grained Visual Classification (FGVC) is known as a challenging task due to subtle differences among subordinate categories. Many current FGVC approaches focus on identifying and locating discriminative regions by using the attention mechanism, b
Externí odkaz:
http://arxiv.org/abs/2302.10275
Publikováno v:
In Biomedical Signal Processing and Control September 2024 95 Part A
Publikováno v:
In Computers in Biology and Medicine December 2022 151 Part A
Publikováno v:
In Neurocomputing 15 March 2014 127:190-199
Publikováno v:
The Journal of The Textile Institute. 110:911-915
A content-based lace fabric image retrieval system using texture and shape features is presented in this article. The retrieval system consists of two steps: registration and identification. During...
Publikováno v:
The Journal of The Textile Institute. 110:487-495
A new fabric defect detection algorithm is presented in this paper. Instead of a Gabor filter bank, an optimal Elliptical Gabor filter (EGF) is used in the proposed algorithm. For a given non-defec...
Publikováno v:
Journal of Physics: Conference Series. 1651:012079
The Fabric defect detection method based on Cascade Deep Support Vector Data Description (SVDD) is proposed in this paper. The method describes the data by Deep SVDD to realize the correct evaluation between the normal fabric images and the images wi
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