Investigators developed and validated a masked autoencoder deep learning model using vision transformer technology to automate the detection and grading of nuclear cataracts from slit-lamp images.

Abstract: Clustering is a fundamental task in machine learning and data mining. The success of deep learning, especially deep generative models, has given birth to the next generation of clustering - ...

A week ago, Elon Musk announced that Tesla had started Robotaxi rides in Austin “with no safety monitor in the car.” The stock jumped 4%. Headlines celebrated the milestone. But since then, not a ...

Elon Musk celebrated the milestone, but its unclear how many people will be able to ride in Tesla’s newly unsupervised robotaxis in the immediate future. Elon Musk celebrated the milestone, but its ...

This project implements a zero-day attack detection system that identifies previously unknown attacks by analyzing system behavior, network patterns, and application activities. It uses unsupervised ...

Abstract: Unsupervised reinforcement learning (RL) aims to discover diverse behaviors that can accelerate the learning of downstream tasks. Previous methods typically focus on entropy-based ...

Companies investing millions in generative AI may soon find themselves stalled—not by the technology’s limits, but by their people’s. As generative AI becomes more ubiquitous, a paradox has emerged: ...

In a college-entrance-exam landscape long dominated by the SAT and the ACT, a relative newcomer has started to gain traction—especially in red states. The Classic Learning Test, first unveiled a ...

During my years teaching science in middle school, high school and college, some of my students have resisted teaching that educators call higher-order thinking. This includes analysis, creative and ...

ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...