Zobrazeno 1 - 10
of 11 775
pro vyhledávání: '"ZHU, Min"'
Autor:
Cheng, Junlong, Fu, Bin, Ye, Jin, Wang, Guoan, Li, Tianbin, Wang, Haoyu, Li, Ruoyu, Yao, He, Chen, Junren, Li, Jingwen, Su, Yanzhou, Zhu, Min, He, Junjun
Interactive Medical Image Segmentation (IMIS) has long been constrained by the limited availability of large-scale, diverse, and densely annotated datasets, which hinders model generalization and consistent evaluation across different models. In this
Externí odkaz:
http://arxiv.org/abs/2411.12814
Geological carbon sequestration (GCS) involves injecting CO$_2$ into subsurface geological formations for permanent storage. Numerical simulations could guide decisions in GCS projects by predicting CO$_2$ migration pathways and the pressure distribu
Externí odkaz:
http://arxiv.org/abs/2409.16572
Palmprint recognition has emerged as a prominent biometric authentication method, owing to its high discriminative power and user-friendly nature. This paper introduces a novel Cross-Chirality Palmprint Verification (CCPV) framework that challenges t
Externí odkaz:
http://arxiv.org/abs/2409.13056
Recently, finger knuckle prints (FKPs) have gained attention due to their rich textural patterns, positioning them as a promising biometric for identity recognition. Prior FKP recognition methods predominantly leverage first-order feature descriptors
Externí odkaz:
http://arxiv.org/abs/2406.19672
Automated cephalometric landmark detection is crucial in real-world orthodontic diagnosis. Current studies mainly focus on only adult subjects, neglecting the clinically crucial scenario presented by adolescents whose landmarks often exhibit signific
Externí odkaz:
http://arxiv.org/abs/2406.12577
Computational notebooks are widely utilized for exploration and analysis. However, creating slides to communicate analysis results from these notebooks is quite tedious and time-consuming. Researchers have proposed automatic systems for generating sl
Externí odkaz:
http://arxiv.org/abs/2403.09121
Autor:
Ye, Jin, Cheng, Junlong, Chen, Jianpin, Deng, Zhongying, Li, Tianbin, Wang, Haoyu, Su, Yanzhou, Huang, Ziyan, Chen, Jilong, Jiang, Lei, Sun, Hui, Zhu, Min, Zhang, Shaoting, He, Junjun, Qiao, Yu
Segment Anything Model (SAM) has achieved impressive results for natural image segmentation with input prompts such as points and bounding boxes. Its success largely owes to massive labeled training data. However, directly applying SAM to medical ima
Externí odkaz:
http://arxiv.org/abs/2311.11969
Palmprint biometrics garner heightened attention in palm-scanning payment and social security due to their distinctive attributes. However, prevailing methodologies singularly prioritize texture orientation, neglecting the significant texture scale d
Externí odkaz:
http://arxiv.org/abs/2311.11354