IEEE

Evolutionary Adversarial Autoencoder for Unsupervised Anomaly Detection of Industrial Internet of Things

The rapid growth of interconnected smart devices and advanced computing technologies in the industrial Internet of Things (IIoT) has significantly enhanced operational resilience and performance but ...
IEEE

Performance Evaluation of Support Vector Machine and Stacked Autoencoder for Hyperspectral Image Analysis

Abstract: In the world of remote sensing, hyperspectral imaging has emerged as a powerful tool that captures incredibly detailed information about our environment. These images contain hundreds of ...

Small Language Models Outperform Frontier AI On Cost, Speed And Accuracy

Bigger has defined AI from day one. New data says task-specific small models beat frontier LLMs on accuracy, cost and speed — ...

Beckhoff's TwinCAT CoAgent Accelerates Automation Programming with Built-In AI Tools

TwinCAT CoAgent delivers powerful AI-assisted engineering and programming support across every stage of the automation ...
Frontiers

Early detection of brain pathologies through deep learning and advanced neuroimaging approaches

Recent advances in the field of medical imaging and computational neuroscience have transformed the landscape of brain pathology detection. The application ...
CNET

Your Brain Is a Better AI Detector Than Any Tool Out There. Here's How to Use It

AI detection tools promised a clean solution to the internet's growing slop problem. What they've delivered is a coin flip.
GitHub

AESTETIK: AutoEncoder for Spatial Transcriptomics Expression with Topology and Image Knowledge

This model is part of the paper "Representation learning for multi-modal spatially resolved transcriptomics data". Authors: Kalin Nonchev, Sonali Andani, Joanna Ficek-Pascual, Marta Nowak, Bettina ...