An In-Depth Analysis of Domain Adaptation in Computer and Robotic Vision
This review article comprehensively delves into the rapidly evolving field of domain
adaptation in computer and robotic vision. It offers a detailed technical analysis of the …
adaptation in computer and robotic vision. It offers a detailed technical analysis of the …
Data efficient deep learning for medical image analysis: A survey
The rapid evolution of deep learning has significantly advanced the field of medical image
analysis. However, despite these achievements, the further enhancement of deep learning …
analysis. However, despite these achievements, the further enhancement of deep learning …
Unsupervised domain adaptation based on feature and edge alignment for femur X-ray image segmentation
X Jiang, Y Yang, T Su, K Xiao, LD Lu, W Wang… - … Medical Imaging and …, 2024 - Elsevier
The gold standard for diagnosing osteoporosis is bone mineral density (BMD) measurement
by dual-energy X-ray absorptiometry (DXA). However, various factors during the imaging …
by dual-energy X-ray absorptiometry (DXA). However, various factors during the imaging …
Advancing UWF-SLO Vessel Segmentation with Source-Free Active Domain Adaptation and a Novel Multi-Center Dataset
H Wang, X Luo, W Chen, Q Tang, M Xin… - arXiv preprint arXiv …, 2024 - arxiv.org
Accurate vessel segmentation in Ultra-Wide-Field Scanning Laser Ophthalmoscopy (UWF-
SLO) images is crucial for diagnosing retinal diseases. Although recent techniques have …
SLO) images is crucial for diagnosing retinal diseases. Although recent techniques have …
Generalizing deep learning models for medical image classification
M Sarah, L Mathieu, Z Philippe, AL Guilcher… - arXiv preprint arXiv …, 2024 - arxiv.org
Numerous Deep Learning (DL) models have been developed for a large spectrum of
medical image analysis applications, which promises to reshape various facets of medical …
medical image analysis applications, which promises to reshape various facets of medical …
[引用][C] Enhancing classification accuracy of HRF signals in fNIRS using semi-supervised learning and filtering
CH Chen, KK Shyu, YC Wu, CH Hung, PL Lee, CW Jao - 2024 - Elsevier