Le Lézard

Food Allergy Diagnostics are Enhanced by Machine Learning and Deep Learning AI Models

Both machine learning and deep learning AI models show significant improvements over existing clinical criteria of food allergy diagnostics, according to new research being presented at the 2026 AAAAI ...
Scientific Research Publishing

Accuracy and Response Speed of Eye Center Annotation Using Eye Movement Models: Validating the Effectiveness of Eyesight Detection ()

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
IEEE

Hybrid CNN Framework for Enhanced Skin Cancer Detection: Merging Machine Learning and Explainable AI

Abstract: Skin cancer is an important issue for public health and requires accurate and dependable diagnostic systems. The present study intended to develop a hybrid framework for skin cancer ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
IEEE

A Comparative Study of Nabla Tau and SCAR Unlearning Algorithms for CNN-Based Facial Race Classification

Abstract: The proliferation of machine learning (ML) in sensitive domains like facial race classification has created an urgent need for mechanisms to remove data, driven by privacy regulations like ...
IEEE

Enhancing Random Forest Using Genetic Algorithm for Lifelong Machine Learning

Abstract: Learning over time for machine learning (ML) models is emerging as a new field, often called continual learning or lifelong Machine learning (LML). Today, deep learning and neural networks ...
IEEE

Optimization of Algorithm for Network Traffic Anomaly Detection Using Convolutional Neural Networks (CNN)

Abstract: With the rapid development of network technology, network security issues have become particularly prominent, especially in the context of big data and the Internet plus era, traditional ...
GitHub

This repository includes unsupervised (k-means clustering) and supervised (RF and CNN) machine learning models for analyzing complex surface topographies.

Cite as: {Henkel, M., Sprenger, M., and Lieleg, O., Machine learning for small data sets: an exemplary study on the classification of highly complex surface micromorphologies, unpublished work} The ...
Frontiers

Accurate intelligent modeling of mud loss while drilling wells via soft computing methods

Accurate prediction of mud loss volume in drilling operations is a critical challenge in industries such as petroleum engineering and geothermal well construction. Unforeseen mud loss leads to ...