Classification of 4XMM-DR9 sources by machine learning

Sequence function classification by machine learning methods

Medical Image Classification by Supervised Machine Learning

In this paper, Support Vector Machine (SVM) was used to learn image feature characteristics for image classification. Several image visual features describe the shape, edge, and texture of image (including histogram, spatial layout, coherence moment and gabor features) have been employed in this paper to categorize the 500 test images into 46 classes. The result shows that the spatial relations...

ANGEL - Machine Learning Classification

The Automated Network Games Enhancement Layer (ANGEL) project aims to leverage machine learning techniques to automate the classification and isolation of interactive (e.g. games, voice over IP) and noninteractive (e.g. web) traffic. This information is then used to dynamically reconfigure the network to improve the Quality of Service provided to the current interactive traffic flows and subseq...

Diagnosing Breast Cancer by Machine Learning

Background and Aim: Cancer and in particular Breast cancer are among the diseases that have the highest mortality rate in Iran after heart disease. The accurate prognosis for Breast cancer is important, and the presence of various symptoms and features of this disease makes it difficult for doctors to diagnose. This study aimed to identify the factors affecting Breast cancer, modeling and ultim...

Comparison of Machine Learning Algorithms for Broad Leaf Species Classification Using UAV-RGB Images

Abstract: Knowing the tree species combination of forests provides valuable information for studying the forest’s economic value, fire risk assessment, biodiversity monitoring, and wildlife habitat improvement. Fieldwork is often time-consuming and labor-required, free satellite data are available in coarse resolution and the use of manned aircraft is relatively costly. Recently, unmanned aeria...