Zobrazeno 1 - 10
of 371
pro vyhledávání: '"Xiu Shen"'
Autor:
Zhenyu Yang, Xiu Shen, Junyi Jin, Xiaoyan Jiang, Wenqi Pan, Chenyao Wu, Dehong Yu, Ping Li, Wei Feng, Yu Chen
Publikováno v:
Advanced Science, Vol 11, Iss 29, Pp n/a-n/a (2024)
Abstract Photosynthesis, essential for life on earth, sustains diverse processes by providing nutrition in plants and microorganisms. Especially, photosynthesis is increasingly applied in disease treatments, but its efficacy is substantially limited
Externí odkaz:
https://doaj.org/article/79d112868f194d11acdf3199c1cbd727
Publikováno v:
Tobacco Induced Diseases, Vol 22, Iss March, Pp 1-10 (2024)
Introduction Understanding the current burden of stomach cancer linked to smoking and the variations in trends across different locations, is crucial for developing effective prevention strategies. In this study, we present findings on the age-stand
Externí odkaz:
https://doaj.org/article/745e1eb467cd4bebba3a86f031ca5fb6
Publikováno v:
Frontiers in Oncology, Vol 12 (2022)
ObjectiveTrends in the incidence, disability-adjusted life-years (DALYs), and mortality rate of cervical cancer remain unknown.MethodsThe average annual percent changes (AAPCs) and relative risks (RR) in the incidence, DALYs, and mortality rate were
Externí odkaz:
https://doaj.org/article/eaa4352923f140c0b58530de699a6ea0
Our work focuses on tackling large-scale fine-grained image retrieval as ranking the images depicting the concept of interests (i.e., the same sub-category labels) highest based on the fine-grained details in the query. It is desirable to alleviate t
Externí odkaz:
http://arxiv.org/abs/2311.12894
Learning fine-grained embeddings from coarse labels is a challenging task due to limited label granularity supervision, i.e., lacking the detailed distinctions required for fine-grained tasks. The task becomes even more demanding when attempting few-
Externí odkaz:
http://arxiv.org/abs/2311.11019
Fine-Grained Image Recognition (FGIR) is a fundamental and challenging task in computer vision and multimedia that plays a crucial role in Intellectual Economy and Industrial Internet applications. However, the absence of a unified open-source softwa
Externí odkaz:
http://arxiv.org/abs/2310.09600
Autor:
Hu, Feiran, Wang, Peng, Li, Yangyang, Duan, Chenlong, Zhu, Zijian, Wang, Fei, Zhang, Faen, Li, Yong, Wei, Xiu-Shen
The SnakeCLEF2023 competition aims to the development of advanced algorithms for snake species identification through the analysis of images and accompanying metadata. This paper presents a method leveraging utilization of both images and metadata. M
Externí odkaz:
http://arxiv.org/abs/2307.09748
We propose Equiangular Basis Vectors (EBVs) for classification tasks. In deep neural networks, models usually end with a k-way fully connected layer with softmax to handle different classification tasks. The learning objective of these methods can be
Externí odkaz:
http://arxiv.org/abs/2303.11637
Simplicity Bias (SB) is a phenomenon that deep neural networks tend to rely favorably on simpler predictive patterns but ignore some complex features when applied to supervised discriminative tasks. In this work, we investigate SB in long-tailed imag
Externí odkaz:
http://arxiv.org/abs/2302.03264