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 ...

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 ...

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...

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 ...