Zobrazeno 1 - 10
of 439
pro vyhledávání: '"label distribution learning"'
Accurate pneumoconiosis staging via deep texture encoding and discriminative representation learning
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
Accurate pneumoconiosis staging is key to early intervention and treatment planning for pneumoconiosis patients. The staging process relies on assessing the profusion level of small opacities, which are dispersed throughout the entire lung field and
Externí odkaz:
https://doaj.org/article/2bf9d6b497da45a184ddb012bea41cc5
Publikováno v:
IEEE Access, Vol 12, Pp 17679-17689 (2024)
Deep learning-based bone age assessment (BAA) approaches have certain drawbacks, such as ignoring the correlation of age labels and simply assuming that bone development is linearly related to bone age, which can affect the accuracy of predictions. T
Externí odkaz:
https://doaj.org/article/42129c9e95ea4c98ad21d152a9bd40d5
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 1, Pp 965-987 (2023)
Estimating the proportion of land-use types in different regions is essential to promote the organization of a compact city and reduce energy consumption. However, existing research in this area has a few limitations: (1) lack of consideration of lan
Externí odkaz:
https://doaj.org/article/2ea2cddb3f4847bf85427296a39eecfb
Autor:
Wanli Zhao, Shutong Wang, Xiaoguang Wang, Duantengchuan Li, Jing Wang, Chenghang Lai, Xiaoxue Li
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 1, Pp 101869- (2024)
Head pose estimation plays a pivotal role in various applications, including augmented reality and human–computer interaction within intelligent museum environments. Head pose estimation conventionally relies on hard labels. However, acquiring the
Externí odkaz:
https://doaj.org/article/6b8458be25a04cdeb4aab60113d1eee9
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 10, Pp 10094-10108 (2022)
Label distribution learning is a novel machine learning paradigm to deal with label ambiguity, which is the generalization of the traditional single-label learning and multi-label learning paradigms. Though label distribution learning has attracted a
Externí odkaz:
https://doaj.org/article/66308eb6a763441bbc8a1b59465312d3
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 15, Iss 1, Pp 1-17 (2022)
Abstract Text classification is a crucial task in data mining and artificial intelligence. In recent years, deep learning-based text classification methods have made great development. The deep learning methods supervise model training by representin
Externí odkaz:
https://doaj.org/article/64d41a896da848abae7e5941053f0950
Autor:
Shutong Wang, Anran Zhao, Chenghang Lai, Qi Zhang, Duantengchuan Li, Yihua Gao, Liangshan Dong, Xiaoguang Wang
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 7, Pp 101605- (2023)
Facial expression recognition (FER) task in the wild is challenging due to some uncertainties, such as the ambiguity of facial expressions, subjective annotations, and low-quality facial images. A novel model for FER in-the-wild datasets is proposed
Externí odkaz:
https://doaj.org/article/9bc5cbba8b5c4163a20e2b9a0fe77a5e
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