Weicheng Dai
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Explore the profile of Weicheng Dai including associated specialties, affiliations and a list of published articles.
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10
Citations
56
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Recent Articles
1.
You C, Min Y, Dai W, Sekhon J, Staib L, Duncan J
Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit
. 2024 Dec;
2024:26140-26150.
PMID: 39640960
Fine-tuning pre-trained vision-language models, like CLIP, has yielded success on diverse downstream tasks. However, several pain points persist for this paradigm: (i) directly tuning entire pre-trained models becomes both time-intensive...
2.
Liu C, Jin L, Dai W, Dong Y, Jin G
Opt Express
. 2024 Nov;
32(14):24498-24510.
PMID: 39538888
The optimal effectiveness model for optimizing the system parameters was established in this study by combining the optimization function based on the pre-laser Q-switching technique. By introducing boundary conditions to...
3.
You C, Dai W, Liu F, Min Y, Dvornek N, Li X, et al.
IEEE Trans Pattern Anal Mach Intell
. 2024 Sep;
PP.
PMID: 39269798
Recent studies on contrastive learning have achieved remarkable performance solely by leveraging few labels in the context of medical image segmentation. Existing methods mainly focus on instance discrimination and invariant...
4.
You C, Dai W, Min Y, Staib L, Duncan J
Med Image Comput Comput Assist Interv
. 2024 Jun;
14222:561-571.
PMID: 38840671
Integrating high-level semantically correlated contents and low-level anatomical features is of central importance in medical image segmentation. Towards this end, recent deep learning-based medical segmentation methods have shown great promise...
5.
You C, Dai W, Min Y, Staib L, Sekhon J, Duncan J
Med Image Comput Comput Assist Interv
. 2024 May;
14223:194-205.
PMID: 38813456
Medical data often exhibits long-tail distributions with heavy class imbalance, which naturally leads to difficulty in classifying the minority classes (., boundary regions or rare objects). Recent work has significantly...
6.
You C, Dai W, Min Y, Liu F, Clifton D, Kevin Zhou S, et al.
Adv Neural Inf Process Syst
. 2024 May;
36():9984-10021.
PMID: 38813114
For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pairs of samples. This is enabled by...
7.
You C, Dai W, Min Y, Staib L, Duncan J
Inf Process Med Imaging
. 2023 Jul;
13939:641-653.
PMID: 37409056
Contrastive learning has shown great promise over annotation scarcity problems in the context of medical image segmentation. Existing approaches typically assume a balanced class distribution for both labeled and unlabeled...
8.
Wang L, Dai W, Cheng Q, Zhang K, Yang T, Mei T, et al.
ACS Omega
. 2019 Oct;
4(13):15729-15733.
PMID: 31572876
Plastic products have brought us great convenience in our daily life and work. But in the meantime, waste plastics have become solid pollutants in the environment due to its poor...
9.
Dai W, Lu L, Han Y, Wang L, Wang J, Hu J, et al.
ACS Omega
. 2019 Aug;
4(3):4896-4900.
PMID: 31459673
The resource utilization of waste plastic can not only control environmental pollution but can also ease up the problems of lack of energy resources. In this study, molybdenum carbide (MoC)...
10.
Wang L, Zhang K, Pan H, Wang L, Wang D, Dai W, et al.
Nanoscale
. 2018 Oct;
10(40):18936-18941.
PMID: 30302475
Two-dimensional (2D) molybdenum nitride (MoN) nanosheets are promising anode materials for improved lithium-ion batteries. However, the reported synthesis methods of MoN generally rely on high-temperature and complex procedures with low...