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Jan 17, 2025 | 
mdpi.com | Quanhong Ma |Shaohua Jin |Gang Bian |Yang Cui
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Jan 17, 2025 | 
mdpi.com | Quanhong Ma |Shaohua Jin |Gang Bian |Yang Cui
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Oct 20, 2024 | 
mdpi.com | Haixing Xia |Yang Cui |Shaohua Jin |Gang Bian
1. IntroductionAcoustic and optical measurements are commonly used methods for acquiring underwater images. However, optical measurements have a limited range underwater and struggle to capture detailed information of deep-sea environments [1]. In contrast, acoustic measurements are less affected by seawater, and they can be used to obtain comprehensive seabed terrain measurements from close to distant ranges by combining high and low frequencies.
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Oct 17, 2024 | 
mdpi.com | Jui-Che Tu |Yang Cui |Lixia Liu |Chun Yang
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
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Oct 5, 2024 | 
mdpi.com | Haohui Li |Kai Yang |Yang Cui |Lingyun Ai
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Sep 28, 2024 | 
mdpi.com | Guang Liu |Yuhao Chen |Yang Cui |Lifang Shen
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Sep 20, 2024 | 
mdpi.com | Yang Cui |Shaohua Jin |Gang Bian |Haixing Xia
1. IntroductionWith the continuous development and utilization of marine resources, research on seafloor sediment environments has gained increasing attention. Side-scan sonar technology, as a crucial underwater detection method, plays a significant role in marine surveys, underwater archeology, and seafloor geological studies [1,2,3,4].
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Aug 5, 2024 | 
mdpi.com | Chengyang Peng |Shaohua Jin |Gang Bian |Yang Cui
1. IntroductionThe detection and identification of underwater targets, such as shipwrecks, aircraft debris, pipelines, and reefs, are essential tasks in marine science research, resource exploration, and hydrographic surveying. These activities are critically important for maritime traffic safety, the development of marine fisheries, sonar detection, and military operations.
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Jul 24, 2024 | 
journals.plos.org | Yang Cui |Kai Xiang |Yuchen Song |Jinlou Ruan
The first author’s name is spelled incorrectly. The correct name is: Jinlou Ruan. The correct citation is: Ruan J, Cui Y, Xiang K, Song Y (2022) Improved runoff forecasting based on time-varying model averaging method and deep learning. PLOS ONE 17(9): e0274004. https://doi.org/10.1371/journal.pone.0274004Citation: Ruan J, Cui Y, Xiang K, Song Y (2024) Correction: Improved runoff forecasting based on time-varying model averaging method and deep learning. PLoS ONE 19(7): e0307923.
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Jul 21, 2024 | 
biorxiv.org | Xin Zeng |Fuki Gyoja |Yang Cui |Matin Loza
AbstractDespite known single-cell expression profiles in vertebrate retinas, understanding of their developmental and evolutionary expression patterns among homologous cell classes remains limited. We examined and compared approximately 240,000 retinal cells from four species and found significant similarities among homologous cell classes, indicating inherent regulatory patterns.
