Zobrazeno 1 - 10
of 179
pro vyhledávání: '"Mingsheng, Shang"'
Publikováno v:
Heliyon, Vol 10, Iss 18, Pp e37814- (2024)
Convolutional neural network (CNN) has recently become popular for addressing multi-domain image classification. However, most existing methods frequently suffer from poor performance, especially in performance and convergence for various datasets. H
Externí odkaz:
https://doaj.org/article/ecc5f8f7ae1b40f6906c5fddcb8f58e0
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7988 (2024)
Medical ultrasound imaging is extensively employed for diagnostic purposes. However, image quality remains a major obstacle to achieving greater accuracy. Conventional supervised deep learning denoising methods often rely on matched noise-free and no
Externí odkaz:
https://doaj.org/article/f8efa3e8b2e64cd59609128f81b23fa4
Autor:
Wei Cui, Mingsheng Shang
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-27 (2023)
Abstract Rumor posts have received substantial attention with the rapid development of online and social media platforms. The automatic detection of rumor from posts has emerged as a major concern for the general public, the government, and social me
Externí odkaz:
https://doaj.org/article/78c10a5ba2a848398304e55426e8a10d
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-24 (2023)
Abstract The emerging topic of sequential recommender (SR) has attracted increasing attention in recent years, which focuses on understanding and learning the sequential dependencies of user behaviors hidden in the user-item interactions. Previous me
Externí odkaz:
https://doaj.org/article/34346e96e1654b26832b7e20530175f7
Publikováno v:
Journal of Big Data, Vol 9, Iss 1, Pp 1-18 (2022)
Abstract A high-dimensional and incomplete (HDI) matrix is a typical representation of big data. However, advanced HDI data analysis models tend to have many extra parameters. Manual tuning of these parameters, generally adopting the empirical knowle
Externí odkaz:
https://doaj.org/article/885dbf62d8904ab68f81aa35ebde90f7
Autor:
Lan Wang, Mingjiang Xie, Min Pan, Feng He, Bing Yang, Zhigang Gong, Xuke Wu, Mingsheng Shang, Kun Shan
Publikováno v:
Water, Vol 15, Iss 23, p 4104 (2023)
Harmful algal blooms (HABs) have been deteriorating global water bodies, and the accurate prediction of algal dynamics using the modelling method is a challenging research area. High-frequency monitoring and deep learning technology have opened up ne
Externí odkaz:
https://doaj.org/article/3ddd20dba3974d6589c754357aa1d9af
Autor:
Mingjiang Xie, Kun Shan, Sidong Zeng, Lan Wang, Zhigang Gong, Xuke Wu, Bing Yang, Mingsheng Shang
Publikováno v:
Water, Vol 15, Iss 18, p 3191 (2023)
Water level prediction in large dammed rivers is an important task for flood control, hydropower generation, and ecological protection. The variations of water levels in large rivers are traditionally simulated based on hydrological models. Recently,
Externí odkaz:
https://doaj.org/article/ce1425328b7c4af483b5aa431e2f1173
Predicting the future popularity of online content is highly important in many applications. Preferential attachment phenomena is encountered in scale free networks.Under it's influece popular items get more popular thereby resulting in long tailed d
Externí odkaz:
http://arxiv.org/abs/1604.01131
Autor:
Botian Zhou, Kun Shi, Weijia Wang, Dong Zhang, Boqiang Qin, Yunlin Zhang, Baili Dong, Mingsheng Shang
Publikováno v:
Ecological Indicators, Vol 143, Iss , Pp 109435- (2022)
Information on long-term phytoplankton phenology trends is critical for clarifying the responses of aquatic ecosystems to environmental perturbations. However, the trends in the phenological metrics of phytoplankton blooms have not yet been comprehen
Externí odkaz:
https://doaj.org/article/a8403cb6b8cf413880d3b09ba2acaf5c
Autor:
Gangping Bi, Bowen Xiao, Yuanchang Lin, Shaoqiu Yan, Ying Tang, Songxiying He, Mingsheng Shang, Guotian He
Publikováno v:
Nanomaterials, Vol 13, Iss 2, p 298 (2023)
Pressure sensors urgently need high-performance sensing materials in order to be developed further. Sensitivity and creep are regarded as two key indices for assessing a sensor’s performance. For the design and optimization of sensing materials, an
Externí odkaz:
https://doaj.org/article/7ac74246ed644862bffff3dd07cec948