Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Changbin Shao"'
Publikováno v:
AIMS Mathematics, Vol 9, Iss 7, Pp 17504-17530 (2024)
Learning from imbalanced data is a challenging task in the machine learning field, as with this type of data, many traditional supervised learning algorithms tend to focus more on the majority class while damaging the interests of the minority class.
Externí odkaz:
https://doaj.org/article/23cf291005224d8d951cab92b08a252c
Publikováno v:
Electronic Research Archive, Vol 32, Iss 5, Pp 3038-3058 (2024)
Imbalanced data distribution and label correlation are two intrinsic characteristics of multi-label data. This occurs because in this type of data, instances associated with certain labels may be sparse, and some labels may be associated with others,
Externí odkaz:
https://doaj.org/article/e1f2e24019024786981b0cd1b6f9db2a
Publikováno v:
International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023).
Publikováno v:
Journal of Computer-Aided Design & Computer Graphics. 32:1948-1956
Publikováno v:
Biomedical Signal Processing and Control. 75:103528
Publikováno v:
The Journal of Engineering. 2018:1668-1673
The authors argue that the mean of discriminant features calculated across the samples of a class (intra-class samples) cannot perform well for the classification task. The main reason is that the mean feature ignores intra-class membership's differe
Publikováno v:
IJCAI
To address the challenges posed by unknown occlusions, we propose a Biased Feature Learning (BFL) framework for occlusion-invariant face recognition. We first construct an extended dataset using a multi-scale data augmentation method. For model train
Publikováno v:
Powder Metallurgy and Metal Ceramics. 56:473-480
An erosion often occurs, when brazing cemented carbide with Cu–Mn based filler alloy, therefore, the binder phase erosion and interface evolution are systematically investigated. When heating, the binder phase Co dissolves into the molten filler an
Publikováno v:
International Journal of Machine Learning and Cybernetics. 8:1485-1492
Although the subspace-based feature extraction algorithms provided a feasible strategy to deal with the classification of high-dimensional data, most of the existing algorithms are locality-oriented and suffer from many difficulties such as uncertain
Publikováno v:
Multimedia Tools and Applications. 76:6641-6661
The changes in appearance of faces, usually caused by pose, expression and illumination variations, increase data uncertainty in the task of face recognition. Insufficient training samples cannot provide abundant multi-view observations of a face. To