Zobrazeno 1 - 10
of 194
pro vyhledávání: '"Qiming Huang"'
Autor:
Gang Wang, Shuxin Wang, Yixin Liu, Qiming Huang, Shengpeng Li, Shuliang Xie, Jinye Zheng, Jiuyuan Fan
Publikováno v:
International Journal of Coal Science & Technology, Vol 11, Iss 1, Pp 1-17 (2024)
Abstract The viscosity of fracturing fluid and in-situ stress difference are the two important factors that affect the hydraulic fracturing pressure and propagation morphology. In this study, raw coal was used to prepare coal samples for experiments,
Externí odkaz:
https://doaj.org/article/86702fe583f74673b29d53536b6e6e1a
Autor:
Shaofei Wang, Bingqing Bai, Qiming Huang, Yuanyuan Fang, Chenyu Zhang, Xinwen Chen, Jianglong Hong, Lei Jie, Hao Ding, Cui Hu, Hongye Li, Yang Li, Xiaochang Liu, Rutao Hong, Junjun Bao, qiao Mei
Publikováno v:
Endoscopy International Open, Vol 12, Iss 10, Pp E1162-E1170 (2024)
Externí odkaz:
https://doaj.org/article/d61f98a0730248458d3ef82253f04c9e
Publikováno v:
Experimental Hematology & Oncology, Vol 13, Iss 1, Pp 1-3 (2024)
Abstract The generation of radiological results from image data represents a pivotal aspect of medical image analysis. The latest iteration of ChatGPT-4, a large multimodal model that integrates both text and image inputs, including dermatoscopy imag
Externí odkaz:
https://doaj.org/article/96c421b0d0e8452680733de29a3a599c
Autor:
Tianqin Xie, Qiming Huang, Qiulan Huang, Yanting Huang, Shuang Liu, Haixia Zeng, Jianping Liu
Publikováno v:
Stem Cell Research & Therapy, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract Objective In recent years, cell therapy has emerged as a new research direction in the treatment of diabetes. However, the underlying molecular mechanisms of mesenchymal stem cell (MSC) differentiation necessary to form such treatment have n
Externí odkaz:
https://doaj.org/article/a69d0d0292c146e180a3192aacc2e904
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 2, Pp 1791-1805 (2024)
A multi-objective pedestrian tracking method based on you only look once-v8 (YOLOv8) and the improved simple online and real time tracking with a deep association metric (DeepSORT) was proposed with the purpose of coping with the issues of local occl
Externí odkaz:
https://doaj.org/article/66f39c83e41c4d2fa506f2c12f71958b
Publikováno v:
Forests, Vol 15, Iss 7, p 1246 (2024)
Mangroves play a crucial role in improving the water quality of mangrove wetlands. However, current research faces challenges, such as the difficulty in quantifying the impact of mangroves on water quality and the unclear pathways of influence. This
Externí odkaz:
https://doaj.org/article/951bc26ffdcd440dbf0a0233716b5d66
Autor:
Muhammad Hassan, Hao Zhang, Ahmed Ameen Fateh, Shuyue Ma, Wen Liang, Dingqi Shang, Jiaming Deng, Ziheng Zhang, Tsz Kwan Lam, Ming Xu, Qiming Huang, Dongmei Yu, Canyang Zhang, Zhou You, Wei Pang, Chengming Yang, Peiwu Qin
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 1, Pp 257-271 (2023)
Abstract Fundus image captures rear of an eye which has been studied for disease identification, classification, segmentation, generation, and biological traits association using handcrafted, conventional, and deep learning methods. In biological tra
Externí odkaz:
https://doaj.org/article/2d5daa167c4c4997b21818b7bbde196d
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-18 (2022)
Abstract Deep resource extraction has been affected by the complex geological environment of "three highs and one disturbance" for a long time. The surrounding rocks experience strong unloading stress disturbance during the underground resource extra
Externí odkaz:
https://doaj.org/article/c8cdc37256fa4b31abdd8cd6ea585963
Publikováno v:
International Journal of Mining Science and Technology, Vol 32, Iss 2, Pp 387-397 (2022)
To improve the efficiency of coal seam water injection, the influence of nanofluids on coal surface wettability was studied based on the nano drag reduction and injection enhancement technology in the field of tertiary oil recovery. The composition o
Externí odkaz:
https://doaj.org/article/f3f4e9ab8c434bf0a08d2906d0f9875c
Autor:
Yang Liu, Lijin Lian, Ersi Zhang, Lulu Xu, Chufan Xiao, Xiaoyun Zhong, Fang Li, Bin Jiang, Yuhan Dong, Lan Ma, Qiming Huang, Ming Xu, Yongbing Zhang, Dongmei Yu, Chenggang Yan, Peiwu Qin
Publikováno v:
Frontiers in Computer Science, Vol 4 (2022)
Deep learning techniques have shown great potential in medical image processing, particularly through accurate and reliable image segmentation on magnetic resonance imaging (MRI) scans or computed tomography (CT) scans, which allow the localization a
Externí odkaz:
https://doaj.org/article/20a3ed4972464d8f83e7d58651c856dc