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Found 6 papers, 2 papers with code
PGU-net+: Progressive Growing of U-net+ for Automated Cervical Nuclei Segmentation
The experimental results show that the PGU-net+ has superior accuracy than the previous state-of-the-art methods on cervical nuclei segmentation.
Automated Segmentation of Cervical Nuclei in Pap Smear Images using Deformable Multi-path Ensemble Model
Pap smear testing has been widely used for detecting cervical cancers based on the morphology properties of cell nuclei in microscopic image.
Semi-supervised Sparse Representation with Graph Regularization for Image Classification
Image classification is a challenging problem for computer in reality.
Skin disease diagnosis with deep learning: a review
As an important part of this article, we then review the literature involving deep learning methods for skin disease diagnosis from several aspects according to the specific tasks.
propnet: Propagating 2D Annotation to 3D Segmentation for Gastric Tumors on CT Scans
This model consists of a proposing stage for coarse segmentation and a refining stage for improved segmentation, using two-way branches for enhanced performance and an up-down strategy for efficiency.
Quantitative Analysis of Molecular Transport in the Extracellular Space Using Physics-Informed Neural Network
Consequently, the proposed method allows for the quantitative analysis and identification of the specific pattern of molecular transport within the ECS through the calculation of the Peclet number.
