Semi-supervised learning (SSL) has emerged as a promising paradigm for medical image classification, addressing the critical challenge of limited labeled data in healthcare where expert annotation is ...

Abstract: Overcoming class imbalance is a critical challenge for graph-based semi-supervised classification methods. In this letter, we address this issue from the perspective of graph filtering and ...

Quantifying natural behavior from video recordings is a key component in ethological studies. Markerless pose estimation methods have provided an important step toward that goal by automatically ...

A research team led by Prof. Wang Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...

This paper proposes a GIS-based approach to classifying land cover using key morphometric indicators—slope, aspect, and elevation. The study focuses on the Chepelarska River basin in the Western ...

Multi-view learning is gradually becoming a well-established domain within machine learning that tackles problems involving the availability of multiple views or sources of data. Existing multi-view ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

Abstract: The existing methods for diagnosing partial discharge (PD) insulation defects in gas-insulated switchgear (GIS) can only achieve a high identification accuracy (ACC) if sufficient labeled ...

Applied Machine Learning projects includes: a supervised machine learning model to classify emails from the given dataset as spam and not-spam. 2.

This notebook tested the performance of the following scikit-learn models: Logistic Regression, Multilayer Perception, Naive Bayes, KNN, and Random Forest Classifier in classifying whether a person ...