IEEE

Forest Tree Species Classification Based on Deep Ensemble Learning by Fusing High-Resolution, Multitemporal, and Hyperspectral Multisource Remote Sensing Data

Abstract: Forest tree species classification has great significance for sustainable development of forest resource. Multisource remote sensing data provide abundant temporal, spatial, and spectral ...
Opinion

How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
IEEE

Hierarchical Multi-Class and Multi-Label Text Classification for Crime Report: A Traditional Machine Learning Approach

Abstract: Large amounts of digital data are produced daily through society’s use of government and private companies. Digital transformation contributes to the increasing amount of structured and ...
The Lancet

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study ...

aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...
ahajournals.org

Abstract 4368538: Fusion Machine Learning Architectures for Improving ECG classification of acute coronary events

Introduction: Acute coronary syndrome (ACS) is a life-threatening emergency, with occlusion myocardial infarction (OMI) requiring rapid diagnosis and treatment. The 12-lead ECG remains the primary ...
Frontiers

A machine learning approach for saddle height classification in cycling

Saddle height is an important factor in bike fitting because it correlates with cycling efficiency and the risk of injuries. Conventional approaches use anthropometric parameters and joint angles as ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...