Zobrazeno 1 - 10
of 568
pro vyhledávání: '"Junyu Dong"'
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 3116-3134 (2024)
Facial palsy evaluation (FPE) aims to assess facial palsy severity of patients, which plays a vital role in facial functional treatment and rehabilitation. The traditional manners of FPE are based on subjective judgment by clinicians, which may ultim
Externí odkaz:
https://doaj.org/article/924d0e1ff9174e8d82e850eba7b4c394
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 9, p 1616 (2024)
Object segmentation, a key type of image segmentation, focuses on detecting and delineating individual objects within an image, essential for applications like robotic vision and augmented reality. Despite advancements in deep learning improving obje
Externí odkaz:
https://doaj.org/article/2e49cab6eacd4c0181bf36801671ea05
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 7, p 1216 (2024)
Vision-based underwater exploration is crucial for marine research. However, the degradation of underwater images due to light attenuation and scattering poses a significant challenge. This results in the poor visual quality of underwater images and
Externí odkaz:
https://doaj.org/article/e8908f04e50d42fa9e1f73e7f533feb4
Autor:
Hafiza Sadia Nawaz, Junyu Dong
Publikováno v:
IEEE Access, Vol 11, Pp 37976-37986 (2023)
This study examines the difficulty in measuring temporal moments by using natural language (TMMNL) in the untrimmed video. The purpose of TMMNL is to use natural language query to find a specific moment within a lengthy video. It’s a challenging ta
Externí odkaz:
https://doaj.org/article/05954b397e56433d82267d7b2d3232e4
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 3045-3059 (2023)
Removing the noise and improving the visual quality of hyperspectral images (HSIs) is challenging in academia and industry. Great efforts have been made to leverage local, global, or spectral context information for HSI denoising. However, existing m
Externí odkaz:
https://doaj.org/article/f1b0880017254785ab6b82a631fa8868
Publikováno v:
Algorithms, Vol 16, Iss 12, p 555 (2023)
Ensemble learning, online learning and deep learning are very effective and versatile in a wide spectrum of problem domains, such as feature extraction, multi-class classification and retrieval. In this paper, combining the ideas of ensemble learning
Externí odkaz:
https://doaj.org/article/8d5b1576a50d480fbea31397aeb4ca0c
Autor:
Shasha Song, Isaac R. Santos, Huaming Yu, Faming Wang, William C. Burnett, Thomas S. Bianchi, Junyu Dong, Ergang Lian, Bin Zhao, Lawrence Mayer, Qingzhen Yao, Zhigang Yu, Bochao Xu
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-10 (2022)
The authors map the global distribution of the mixed layer in coastal ocean sediments, based on a neural network model. These observations reveal that mixing can accelerate organic matter degradation and reduce carbon storage in the coastal ocean.
Externí odkaz:
https://doaj.org/article/c803c98ce3bb45aeb3c51303be24b617
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 1823-1836 (2022)
Synthetic aperture radar (SAR) image change detection is a vital yet challenging task in the field of remote sensing image analysis. Most previous works adopt a self-supervised method which uses pseudolabeled samples to guide subsequent training and
Externí odkaz:
https://doaj.org/article/bceaca2b344f4cf281c4d2e55b092ddf
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 2667-2680 (2022)
Benefited from the rapid and sustainable development of synthetic aperture radar (SAR) sensors, change detection from SAR images has received increasing attentions over the past few years. Existing unsupervised deep learning-based methods have made g
Externí odkaz:
https://doaj.org/article/a96c28043b9941ee9afa2566e7d2f838
Autor:
Yongkang Zhao, Guodong Zheng, Huaizhi Bo, Yijing Wang, Junyu Dong, Changchao Li, Yan Wang, Shuwan Yan, Kang Liu, Zhiliang Wang, Jian Liu
Publikováno v:
PLoS ONE, Vol 18, Iss 2, p e0282014 (2023)
The content and composition of soil organic carbon (SOC) can characterize soil carbon storage capacity, which varies significantly between habitats. Ecological restoration in coal mining subsidence land forms a variety of habitats, which are ideal to
Externí odkaz:
https://doaj.org/article/0c3041d4b511449995ffce574a65c61e