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Found 9 papers, 0 papers with code
PSHop: A Lightweight Feed-Forward Method for 3D Prostate Gland Segmentation
Automatic prostate segmentation is an important step in computer-aided diagnosis of prostate cancer and treatment planning.
PCa-RadHop: A Transparent and Lightweight Feed-forward Method for Clinically Significant Prostate Cancer Segmentation
Deep learning (DL) models achieve a high segmentation performance, although require a large model size and complexity.
A Comprehensive Overview of Computational Nuclei Segmentation Methods in Digital Pathology
Nuclei segmentation is an important task, as it detects the nuclei cells over background tissue and gives rise to the topology, size, and count of nuclei which are determinant factors for cancer detection.
Learning Scene Flow With Skeleton Guidance For 3D Action Recognition
Among the existing modalities for 3D action recognition, 3D flow has been poorly examined, although conveying rich motion information cues for human actions.
LGSQE: Lightweight Generated Sample Quality Evaluatoin
Despite prolific work on evaluating generative models, little research has been done on the quality evaluation of an individual generated sample.
Statistical Attention Localization (SAL): Methodology and Application to Object Classification
SAL consists of three steps: 1) preliminary attention window selection via decision statistics, 2) attention map refinement, and 3) rectangular attention region finalization.
HUNIS: High-Performance Unsupervised Nuclei Instance Segmentation
The second stage exploits the segmentation masks obtained in the first stage and leverages color and shape distributions for a more accurate segmentation.
Unsupervised Data-Driven Nuclei Segmentation For Histology Images
An unsupervised data-driven nuclei segmentation method for histology images, called CBM, is proposed in this work.
E-PixelHop: An Enhanced PixelHop Method for Object Classification
Forth, pixel-level decisions from each hop and from each color subspace are fused together for image-level decision.
