Zobrazeno 1 - 10
of 2 364
pro vyhledávání: '"Chen, Zhihao"'
Current road damage detection methods, relying on manual inspections or sensor-mounted vehicles, are inefficient, limited in coverage, and often inaccurate, especially for minor damages, leading to delays and safety hazards. To address these issues a
Externí odkaz:
http://arxiv.org/abs/2409.01604
Autor:
Liu, Qichun, Lin, Jie, Wang, Xiaofeng, Dai, Zhibin, Sun, Yongkang, Xi, Gaobo, Mo, Jun, Liu, Jialian, Yan, Shengyu, Filippenko, Alexei V., Brink, Thomas G., Yang, Yi, Patra, Kishore C., Cai, Yongzhi, Chen, Zhihao, Chen, Liyang, Guo, Fangzhou, Jiang, Xiaojun, Li, Gaici, Li, Wenxiong, Lin, Weili, Miao, Cheng, Ma, Xiaoran, Peng, Haowei, Xia, Qiqi, Xiang, Danfeng, Zhang, Jicheng
The Tsinghua University--Ma Huateng Telescopes for Survey (TMTS) started to monitor the LAMOST plates in 2020, leading to the discovery of numerous short-period eclipsing binaries, peculiar pulsators, flare stars, and other variable objects. Here, we
Externí odkaz:
http://arxiv.org/abs/2408.12104
In the field of medical image segmentation, models based on both CNN and Transformer have been thoroughly investigated. However, CNNs have limited modeling capabilities for long-range dependencies, making it challenging to exploit the semantic inform
Externí odkaz:
http://arxiv.org/abs/2408.11289
The semantic segmentation task in pathology plays an indispensable role in assisting physicians in determining the condition of tissue lesions. With the proposal of Segment Anything Model (SAM), more and more foundation models have seen rapid develop
Externí odkaz:
http://arxiv.org/abs/2408.03651
Cloth-changing person re-identification (CC-ReID) aims to retrieve specific pedestrians in a cloth-changing scenario. Its main challenge is to disentangle the clothing-related and clothing-unrelated features. Most existing approaches force the model
Externí odkaz:
http://arxiv.org/abs/2407.10694
Medical image segmentation has been significantly advanced with the rapid development of deep learning (DL) techniques. Existing DL-based segmentation models are typically discriminative; i.e., they aim to learn a mapping from the input image to segm
Externí odkaz:
http://arxiv.org/abs/2407.03548
Source-Free Unsupervised Domain Adaptation (SFUDA) has recently become a focus in the medical image domain adaptation, as it only utilizes the source model and does not require annotated target data. However, current SFUDA approaches cannot tackle th
Externí odkaz:
http://arxiv.org/abs/2405.16102
Flat-top beam, known for its ability to generate a consistently even irradiation area, holds vast utility in many fields of scientific and industrial applications. In this paper, a reflective laser beam shaping method based on two axisymmetric aspher
Externí odkaz:
http://arxiv.org/abs/2405.09048
Automated radiology reporting holds immense clinical potential in alleviating the burdensome workload of radiologists and mitigating diagnostic bias. Recently, retrieval-based report generation methods have garnered increasing attention due to their
Externí odkaz:
http://arxiv.org/abs/2405.04175
Autor:
Wang, Chenhui, Chen, Tao, Chen, Zhihao, Huang, Zhizhong, Jiang, Taoran, Wang, Qi, Shan, Hongming
Despite their impressive generative performance, latent diffusion model-based virtual try-on (VTON) methods lack faithfulness to crucial details of the clothes, such as style, pattern, and text. To alleviate these issues caused by the diffusion stoch
Externí odkaz:
http://arxiv.org/abs/2404.14162