Data retrieval and embeddings enhancements from MongoDB set the stage for a year of specialized AI

Data retrieval and embeddings enhancements from MongoDB set the stage for a year of specialized AI - SiliconANGLE ...

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
Devdiscourse

AI-driven rainfall forecasting shows major gains in predicting flood-triggering storms

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
Asianet Newsable on MSN

What companies expect in 2026: AI skills, machine learning, and responsible AI

Discover the top AI skills in high demand for 2026. Learn about machine learning, generative AI, and other essential ...
EurekAlert!

Machine learning revolutionizes design of green solvents for carbon capture: a new era for ionic liquid development

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green ...
BMJ Open

Development and evaluation of a diagnostic aiding tool for differentiating tropical fevers using artificial intelligence approach: a study protocol from tertiary care hospital ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
IEEE

The Impact of Feature Scaling in Machine Learning: Effects on Regression and Classification Tasks

Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...
techxplore

Overparameterized neural networks: Feature learning precedes overfitting, research finds

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...
Frontiers

Enhanced SQL injection detection using chi-square feature selection and machine learning classifiers

Computational and Communication Science and Engineering (CoCSE), The Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania In the face of increasing cyberattacks, ...
IEEE

Machine-Learning-Based Urban Path Loss Prediction at 900 MHz: Principal Component Analysis, Clustering, Feature Importance and Regression

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...