InfoWorld

How self-learning AI agents will reshape operational workflows

AI agents trained on their own experiences have the potential to revolutionize operations. Practical applications are already ...
Ophthalmology Advisor

Deep Learning Model Differentiates Neuroinflammatory Disorders

Researchers evaluated whether a deep learning model could distinguish between autoimmune neuroinflammatory disorders based on ...
Sports Illustrated

Bo Nix Gives Blunt Take on Brutal Missed Deep Throws in Chargers Loss

The Denver Broncos came up short again on the road in Sunday's 23-20 loss to the Los Angeles Chargers. In back-to-back weeks, the Broncos squandered a fourth-quarter lead, and left the field on the ...
The Conversation

5 ways students can think about learning so that they can learn more − and how their teachers can help

Jerrid Kruse receives funding from the National Science Foundation, the NASA Iowa Space Grant Consortium, and the William G. Stowe Foundation. During my years teaching science in middle school, high ...
IEEE

READ3D-Net: Residual Autoencoder and GAN-Based 3-D Convolutional Network for Anomaly Detection

Abstract: Video anomaly detection (VAD) is of great importance for a variety of real-time applications in video surveillance. Most deep learning-based anomaly detection algorithms adopt a one-class ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
IEEE

Self-Supervised Learning Meets Custom Autoencoder Classifier: A Semi-Supervised Approach for Encrypted Traffic Anomaly Detection

Abstract: The widespread adoption of encryption in computer networks has made detecting malicious traffic, especially at network perimeters, increasingly challenging. As packet contents are concealed, ...
GitHub

Enhancing EV Cost Prediction Using AutoEncoder-Based Feature Learning

Electric Vehicle (EV) cost prediction involves analyzing complex, high-dimensional data that often contains noise, multicollinearity, and irrelevant features. Traditional regression models struggle to ...