News-Medical.Net

Advancing 3D imaging, automation, and phenotypic discovery with AI-driven high-content screening

In this interview, AZoLife Sciences speaks with Boyd Butler, a microscopy and high-content screening expert at Molecular ...
IEEE

Segmentation and Detection of Tumor in MRI images Using CNN and SVM Classification

Abstract: Among cerebrum tumors, gliomas are the most well-known what's more, forceful, prompting a short future in their most noteworthy review. In this way, treatment arranging is a key stage to ...
IEEE

K-means Clustering and SVM for Plant Leaf Disease Detection and Classification

Abstract: The role image processing role is inevitable in the computer vision, robotics, agriculture, and medical field. This work proposes K-means clustering algorithm for the detection of leaf ...
www.cs.utexas.edu

Computer Vision

This is an intro course in computer vision. It is intended for upper-level undergraduate students. Computer vision is an interdisciplinary field that deals with how computers can achieve high-level ...
GitHub

Awesome Decision, Classification, and Regression Tree Research Papers

Les E. Atlas, Ronald A. Cole, Jerome T. Connor, Mohamed A. El-Sharkawi, Robert J. Marks II, Yeshwant K. Muthusamy, Etienne Barnard [Paper] ...
Frontiers

3D Inundation Mapping: A Comparison Between Deep Learning Image Classification and Geomorphic Flood Index Approaches

Inundation mapping is a critical task for damage assessment, emergency management, and prioritizing relief efforts during a flooding event. Remote sensing has been an effective tool for interpreting ...
GitHub

optic-disc-segmentation

This DR detection methodology has six steps: preprocessing, segmentation of blood vessels, segmentation of OD, detection of MAs and hemorrhages, feature extraction and classification. For segmentation ...