Zobrazeno 1 - 10
of 777
pro vyhledávání: '"Wang Shiyi"'
Publikováno v:
Gongye shui chuli, Vol 44, Iss 11, Pp 74-81 (2024)
The treatment of acidic desulphurization wastewater is challenging due to its high acidity and complex composition. Typically, acidic desulphurization wastewater is treated as high-salt wastewater after alkali neutralization, leading to issues such a
Externí odkaz:
https://doaj.org/article/5e81de108280456aa18fb52190df4ed2
Publikováno v:
Guoji Yanke Zazhi, Vol 24, Iss 1, Pp 101-105 (2024)
Preschool age(3-6 years old)is a critical period for visual development, and it is crucial to detect and treat visual problems in preschool children as early as possible. Visual acuity charts are important tools for screening visual issues in childre
Externí odkaz:
https://doaj.org/article/e9922dff2b68440087c8b4b00ee54b4b
Autor:
Wang Shiyi
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In recent years, the examination of literary creation through the lens of the natural geographic environment has emerged as a focal point in literary studies. This study designates China’s geographic environment as the independent variable and anci
Externí odkaz:
https://doaj.org/article/333e4b52b05f4e1a841e334ba5561008
Autor:
Zhu, Yuxuan, Wang, Shiyi, Zhong, Wenqing, Shen, Nianchen, Li, Yunqi, Wang, Siqi, Li, Zhiheng, Wu, Cathy, He, Zhengbing, Li, Li
Artificial intelligence (AI) plays a crucial role in autonomous driving (AD) research, propelling its development towards intelligence and efficiency. Currently, the development of AD technology follows two main technical paths: modularization and en
Externí odkaz:
http://arxiv.org/abs/2409.14165
Autor:
Syahmi, Amir, Lu, Xiangrong, Li, Yinxuan, Yao, Haoxuan, Jiang, Hanjun, Acharya, Ishita, Wang, Shiyi, Nan, Yang, Xing, Xiaodan, Yang, Guang
Recent advancements in medical imaging and artificial intelligence (AI) have greatly enhanced diagnostic capabilities, but the development of effective deep learning (DL) models is still constrained by the lack of high-quality annotated datasets. The
Externí odkaz:
http://arxiv.org/abs/2409.03087
Autor:
Wang, Shiyi, Nan, Yang, Zhang, Sheng, Felder, Federico, Xing, Xiaodan, Fang, Yingying, Del Ser, Javier, Walsh, Simon L F, Yang, Guang
In pulmonary tracheal segmentation, the scarcity of annotated data is a prevalent issue in medical segmentation. Additionally, Deep Learning (DL) methods face challenges: the opacity of 'black box' models and the need for performance enhancement. Our
Externí odkaz:
http://arxiv.org/abs/2407.03542
Autor:
Zhang, Sheng, Nan, Yang, Fang, Yingying, Wang, Shiyi, Xing, Xiaodan, Gao, Zhifan, Yang, Guang
Automatic lung organ segmentation on CT images is crucial for lung disease diagnosis. However, the unlimited voxel values and class imbalance of lung organs can lead to false-negative/positive and leakage issues in advanced methods. Additionally, som
Externí odkaz:
http://arxiv.org/abs/2406.16189
In the field of medical imaging, particularly in tasks related to early disease detection and prognosis, understanding the reasoning behind AI model predictions is imperative for assessing their reliability. Conventional explanation methods encounter
Externí odkaz:
http://arxiv.org/abs/2406.15182
Each medical segmentation task should be considered with a specific AI algorithm based on its scenario so that the most accurate prediction model can be obtained. The most popular algorithms in medical segmentation, 3D U-Net and its variants, can dir
Externí odkaz:
http://arxiv.org/abs/2402.07403
Autor:
Nan, Yang, Xing, Xiaodan, Wang, Shiyi, Tang, Zeyu, Felder, Federico N, Zhang, Sheng, Ledda, Roberta Eufrasia, Ding, Xiaoliu, Yu, Ruiqi, Liu, Weiping, Shi, Feng, Sun, Tianyang, Cao, Zehong, Zhang, Minghui, Gu, Yun, Zhang, Hanxiao, Gao, Jian, Wang, Pingyu, Tang, Wen, Yu, Pengxin, Kang, Han, Chen, Junqiang, Lu, Xing, Zhang, Boyu, Mamalakis, Michail, Prinzi, Francesco, Carlini, Gianluca, Cuneo, Lisa, Banerjee, Abhirup, Xing, Zhaohu, Zhu, Lei, Mesbah, Zacharia, Jain, Dhruv, Mayet, Tsiry, Yuan, Hongyu, Lyu, Qing, Qayyum, Abdul, Mazher, Moona, Wells, Athol, Walsh, Simon LF, Yang, Guang
Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway trees remains prohibitively time-consuming. While significant efforts have been made
Externí odkaz:
http://arxiv.org/abs/2312.13752