Zobrazeno 1 - 10
of 276
pro vyhledávání: '"Zhang, JiaJin"'
Autor:
Song, Xinrui, Zhang, Jiajin, Yan, Pingkun, Hahn, Juergen, Kruger, Uwe, Mohamed, Hisham, Wang, Ge
The integration of artificial intelligence (AI) chatbots into higher education marks a shift towards a new generation of pedagogical tools, mirroring the arrival of milestones like the internet. With the launch of ChatGPT-4 Turbo in November 2023, we
Externí odkaz:
http://arxiv.org/abs/2407.05810
Accurate prediction of Cardiovascular disease (CVD) risk in medical imaging is central to effective patient health management. Previous studies have demonstrated that imaging features in computed tomography (CT) can help predict CVD risk. However, CT
Externí odkaz:
http://arxiv.org/abs/2405.18533
In medical image analysis, the expertise scarcity and the high cost of data annotation limits the development of large artificial intelligence models. This paper investigates the potential of transfer learning with pre-trained vision-language models
Externí odkaz:
http://arxiv.org/abs/2405.15728
Autor:
Zhang, Jiajin, Chao, Hanqing, Dhurandhar, Amit, Chen, Pin-Yu, Tajer, Ali, Xu, Yangyang, Yan, Pingkun
Domain shift is a common problem in clinical applications, where the training images (source domain) and the test images (target domain) are under different distributions. Unsupervised Domain Adaptation (UDA) techniques have been proposed to adapt mo
Externí odkaz:
http://arxiv.org/abs/2309.01207
Autor:
Zhao, Junbo, Ning, Xuefei, Liu, Enshu, Ru, Binxin, Zhou, Zixuan, Zhao, Tianchen, Chen, Chen, Zhang, Jiajin, Liao, Qingmin, Wang, Yu
Predictor-based Neural Architecture Search (NAS) employs an architecture performance predictor to improve the sample efficiency. However, predictor-based NAS suffers from the severe ``cold-start'' problem, since a large amount of architecture-perform
Externí odkaz:
http://arxiv.org/abs/2302.00932
Autor:
Zhang, Jiajin, Chao, Hanqing, Dhurandhar, Amit, Chen, Pin-Yu, Tajer, Ali, Xu, Yangyang, Yan, Pingkun
Domain generalization (DG) aims to train a model to perform well in unseen domains under different distributions. This paper considers a more realistic yet more challenging scenario,namely Single Domain Generalization (Single-DG), where only a single
Externí odkaz:
http://arxiv.org/abs/2212.00850
Regression plays an essential role in many medical imaging applications for estimating various clinical risk or measurement scores. While training strategies and loss functions have been studied for the deep neural networks in medical image classific
Externí odkaz:
http://arxiv.org/abs/2207.05231
Publikováno v:
In Neuroscience and Biobehavioral Reviews December 2024 167
Autor:
Hao, Xuedi1,2 (AUTHOR) haoxd@cumtb.edu.cn, Zhang, Jiajin1 (AUTHOR), Wen, Rusen1 (AUTHOR), Gao, Chuan1 (AUTHOR), Xu, Xianlei3 (AUTHOR), Ge, Shirong1,2 (AUTHOR), Zhang, Yiming1 (AUTHOR), Wang, Shuyang1 (AUTHOR)
Publikováno v:
Sensors (14248220). Sep2024, Vol. 24 Issue 17, p5766. 15p.
Publikováno v:
In Meta-Radiology September 2024 2(3)