IEEE

Semi-Supervised Graph Constraint Dual Classifier Network With Unknown Class Feature Learning for Hyperspectral Image Open-Set Classification

Abstract: In view of the practical value of open datasets of hyperspectral images (HSIs), HSI open-set classification (OSC) has attracted more and more attention. Existing HSI OSC methods are usually ...
GitHub

NabidAlam/road-to-machine-learning

Choose your path! This repository prepares you for multiple ML/AI careers. Select your target role to see a customized learning path: Role Focus Est. Time Key Modules ...
Frontiers

Tackling fraud detection with an enhanced Kepler optimization and ghost opposition-based learning

Introduction: The growing prevalence of fraud and malware, fueled by increased online activity and digital transactions, has exposed the shortcomings of conventional detection systems, particularly in ...
Hosted on MSN

Supervised learning made easy: Real-world example explained

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...
IEEE

SSD: Self-Supervised Distillation for Heterophilic Graph Representation Learning

Abstract: Graph Knowledge Distillation (GKD) has made remarkable progress in graph representation learning in recent years. Despite its great success, GKD often obeys the label-dependence manner, ...