High-level semantic feature matters few-shot unsupervised domain adaptation

no code implementations • 5 Jan 2023 • Lei Yu, Wanqi Yang, Shengqi Huang, Lei Wang, Ming Yang

However, the goal of FS-UDA and FSL are relevant yet distinct, since FS-UDA aims to classify the samples in target domain rather than source domain.

Few-Shot Learning Unsupervised Domain Adaptation +1

Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse Similarity Encoding

no code implementations • 6 Aug 2021 • Shengqi Huang, Wanqi Yang, Lei Wang, Luping Zhou, Ming Yang

Inspired by the recent local descriptor based few-shot learning (FSL), our general UDA model is fully built upon local descriptors (LDs) for image classification and domain adaptation.

Few-Shot Learning Image Classification +1

Learning-based Computer-aided Prescription Model for Parkinson's Disease: A Data-driven Perspective

no code implementations • 31 Jul 2020 • Yinghuan Shi, Wanqi Yang, Kim-Han Thung, Hao Wang, Yang Gao, Yang Pan, Li Zhang, Dinggang Shen

Then, we build a novel computer-aided prescription model by learning the relation between observed symptoms and prescription drug.

Class Distribution Alignment for Adversarial Domain Adaptation

no code implementations • 20 Apr 2020 • Wanqi Yang, Tong Ling, Chengmei Yang, Lei Wang, Yinghuan Shi, Luping Zhou, Ming Yang

To address this issue, we propose a novel approach called Conditional ADversarial Image Translation (CADIT) to explicitly align the class distributions given samples between the two domains.

General Classification Translation +1

Interactive Medical Image Segmentation via Point-Based Interaction and Sequential Patch Learning

1 code implementation • 27 Apr 2018 • Jinquan Sun, Yinghuan Shi, Yang Gao, Lei Wang, Luping Zhou, Wanqi Yang, Dinggang Shen

In this paper, we present a novel method for interactive medical image segmentation with the following merits.

Image Segmentation Medical Image Segmentation +2