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pro vyhledávání: '"Hao-Zhen Shen"'
Publikováno v:
Remote Sensing, Vol 14, Iss 24, p 6308 (2022)
Data augmentation (DA) is an effective way to enrich the richness of data and improve a model’s generalization ability. It has been widely used in many advanced vision tasks (e.g., classification, recognition, etc.), while it can hardly be seen in
Externí odkaz:
https://doaj.org/article/e9483ee3af18477bb3d750481f88c904
Publikováno v:
Remote Sensing, Vol 14, Iss 14, p 3338 (2022)
Hyperspectral images (HSIs) are frequently contaminated by different noises (Gaussian noise, stripe noise, deadline noise, impulse noise) in the acquisition process as a result of the observation environment and imaging system limitations, which make
Externí odkaz:
https://doaj.org/article/f913cfa2eec044fe8b731f79af929387
Autor:
Hao-Zhen Shen, Jiancheng Luo, Chao Wang, Chuan-Sheng Yang, Fan Fan, Mingwen Shao, Liang-Jian Deng
Publikováno v:
Knowledge-Based Systems. 228:107279
Traditional dehazing convolutional neural networks (CNNs) learn the feature maps only from hazy images to the corresponding hazy-free ones, which usually lead to some important feature loss like texture information. The paper proposes an effective ed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91258e6acb03567e79a23c2ef9a1e3e2
https://doi.org/10.1016/j.knosys.2021.107279
https://doi.org/10.1016/j.knosys.2021.107279