A5103106846- Multimodal Machine Learning Applications
- Medical Image Segmentation Techniques
- Radiomics and Machine Learning in Medical Imaging
- Domain Adaptation and Few-Shot Learning
- COVID-19 diagnosis using AI
- AI in cancer detection
University of Shanghai for Science and Technology
2023
Abstract Conventional model transfer techniques, requiring the labelled source data, are not applicable in privacy‐protected medical fields. For challenging scenarios, recent data‐free domain adaptation (SFDA) has become a mainstream solution but losing focus on inter‐sample class information. This paper proposes new Credible Local Context Representation approach for SFDA. Our main idea is to exploit credible local context more discriminative representation. Specifically, we enhance model's...
Few-shot Semantic Segmentation(FSS)aim to adapt a pre-trained model new classes with as few single labeled training sample per class. The existing prototypical work used in natural image scenarios biasedly focus on capturing foreground's discrimination while employing simplistic representation for background, grounded the inherent observation separation between foreground and background. However, this paradigm is not applicable medical images where background share numerous visual features,...