Zobrazeno 1 - 10
of 457
pro vyhledávání: '"caiming zhang"'
Publikováno v:
IEEE Access, Vol 12, Pp 6615-6627 (2024)
Saliency detection is increasingly a crucial task in the computer vision area. In previous graph-based saliency detection, superpixels are usually regarded as the primary processing units to enhance computational efficiency. Nevertheless, most method
Externí odkaz:
https://doaj.org/article/5b7b10d4fb3942e4bc8a218edec60b47
Publikováno v:
Graphical Models, Vol 130, Iss , Pp 101210- (2023)
This paper aims at extending the method of Zhang et al. (2023) to produce not only portrait bas-reliefs from single photographs, but also high-depth reliefs with reasonable depth ordering. We cast this task as a problem of style-aware photo-to-depth
Externí odkaz:
https://doaj.org/article/8ee129289d304affbca76c319d41d871
Publikováno v:
Applied Sciences, Vol 14, Iss 4, p 1443 (2024)
To handle the task of pointer meter reading recognition, in this paper, we propose a deep network model that can accurately detect the pointer meter dial and segment the pointer as well as the reference points from the located meter dial. Specificall
Externí odkaz:
https://doaj.org/article/7325f83761834e998f503e650702912d
Autor:
Caiming Zhang, Wenhui Chen, Si Pan, Siyu Zhang, Haijing Xie, Zixiang Zhang, Wei Lei, Lili Bao, Yiwen You
Publikováno v:
Cell Death Discovery, Vol 9, Iss 1, Pp 1-14 (2023)
Abstract Reliable detection of circulating small extracellular vesicles (SEVs) and their miRNA cargo has been needed to develop potential specific non-invasive diagnostic and therapeutic marker for cancer metastasis. Here, we detected miR-6750, the p
Externí odkaz:
https://doaj.org/article/149adba90c154aa69adbc6c07b27da81
Autor:
Shengyang Xie, Xiyan Yang, Xingzhi Wang, Fei Huo, Zhongliang Ma, Caiming Zhang, Mengyao Jia, Jiahao Kang, Qinfan Yi, Zisang Huang, Yang Li, Rong Yang
Publikováno v:
Energy Exploration & Exploitation, Vol 41 (2023)
The lacustrine shale in the Da’anzhai member of Jurassic in the central Sichuan Basin is a key exploration target for shale oil and gas resources in China in the future. This paper presents a detailed study of shale rock types and component charact
Externí odkaz:
https://doaj.org/article/b02b4152125a479b8a86060b66b80e1d
Publikováno v:
IET Image Processing, Vol 15, Iss 6, Pp 1359-1370 (2021)
Abstract Coronary artery calcium is a strong and independent marker of atherosclerosis and cardiovascular disease. Typically, the accurate segmentation of computed tomography images of the chest is an important prerequisite and basis for coronary art
Externí odkaz:
https://doaj.org/article/df972ab43b734215bd5ff21251d2ed97
Publikováno v:
IET Image Processing, Vol 15, Iss 3, Pp 598-614 (2021)
Abstract Self‐similarity, a prior of natural images, has attracted much attention. The attribute means that low‐rank group matrices can be constructed from similar image patches. For low‐rank approximation denoising methods based on singular va
Externí odkaz:
https://doaj.org/article/6c737129f35449218f2327a3572ead24
Publikováno v:
Taiyuan Ligong Daxue xuebao, Vol 52, Iss 1, Pp 83-90 (2021)
Coronary artery segmentation is a major step in coronary heart disease computer-aided diagnosis systems, which is used to ensure only the coronary artery region to be processed in subsequent steps. The coronary computed tomography angiography (CCTA)
Externí odkaz:
https://doaj.org/article/e1fd73fc80f24043b36f769c8ecbdad4
Publikováno v:
IEEE Access, Vol 9, Pp 33385-33395 (2021)
Generally, most existing super-resolution (SR) methods do not consider noise, which treats SR reconstruction and denoising as two separate problems and performs separately. However, noise is inevitably introduced in the imaging process. Based on anal
Externí odkaz:
https://doaj.org/article/da62a16d406d46ccae4d8bc5e1c24e71
Publikováno v:
Computational Visual Media, Vol 6, Iss 4, Pp 467-476 (2020)
Abstract This paper proposes a kernel-blending connection approximated by a neural network (KBNN) for image classification. A kernel mapping connection structure, guaranteed by the function approximation theorem, is devised to blend feature extractio
Externí odkaz:
https://doaj.org/article/c6fa81257089448a8e3eb69491b8bcf9