2 citations · 4 across the 6 of their papers we have counts for
6 papers
IELDG: Suppressing Domain-Specific Noise with Inverse Evolution Layers for Domain Generalized Semantic Segmentation
Qizhe Fan, Chaoyu Liu, Zhonghua Qiao +1
Domain Generalized Semantic Segmentation (DGSS) focuses on training a model using labeled data from a source domain, with the goal of achieving robust generalization to unseen targ…
Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks
Chaoyu Liu, Zhonghua Qiao, Chao Li +1
Traditional image processing methods employing partial differential equations (PDEs) offer a multitude of meaningful regularizers, along with valuable theoretical foundations for a…
Immunofluorescence Capillary Imaging Segmentation: Cases Study
Runpeng Hou, Ziyuan Ye, Chengyu Yang +3
Nonunion is one of the challenges faced by orthopedics clinics for the technical difficulties and high costs in photographing interosseous capillaries. Segmenting vessels and filli…
Multi-phase image segmentation by the Allen--Cahn Chan--Vese model
Chaoyu Liu, Zhonghua Qiao, Qian Zhang
This paper proposes an Allen-Cahn Chan-Vese model to settle the multi-phase image segmentation. We first integrate the Allen--Cahn term and the Chan--Vese fitting energy term to es…
An Active Contour Model with Local Variance Force Term and Its Efficient Minimization Solver for Multi-phase Image Segmentation
Chaoyu Liu, Zhonghua Qiao, Qian Zhang
In this paper, we propose an active contour model with a local variance force (LVF) term that can be applied to multi-phase image segmentation problems. With the LVF, the proposed…
Two-phase segmentation for intensity inhomogeneous images by the Allen-Cahn Local Binary Fitting Model
Chaoyu liu, Zhonghua Qiao, Qian Zhang
This paper proposes a new variational model by integrating the Allen-Cahn term with a local binary fitting energy term for segmenting images with intensity inhomogeneity and noise.…