IEEE

TinyML-Based Pothole Detection: A Comparative Analysis of YOLO and FOMO Model Performance

Abstract: Potholes pose a substantial threat in urban settings, leading to vehicular damage and safety risks. Therefore, their prompt identification is essential for effective road maintenance. In ...
GitHub

AML: Adversarial Meta-Learning for Few-Shot Object Detection

This package includes our codes for implementing "Adversarial Meta-Learning for Few-Shot Object Detection". (First Release Date: 2025-04-13) Please refer to mmfewshot ...
NPR

Teachers are using software to see if students used AI. What happens when it's wrong?

Ailsa Ostovitz has been accused of using AI on three assignments in two different classes this school year. "It's mentally exhausting because it's like I know this is my work," says Ostovitz, 17. "I ...
Microsoft

Agent Lightning: Adding reinforcement learning to AI agents without code rewrites

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
Journal of Medical Internet Research

Text-Based Depression Prediction on Social Media Using Machine Learning: Systematic Review and Meta-Analysis

Background: Depression affects more than 350 million people globally. Traditional diagnostic methods have limitations. Analyzing textual data from social media provides new insights into predicting ...
IEEE

Performance Evaluation of different Machine Learning Techniques for Pothole Detection

Abstract: A pothole is an oval-shaped depression in the surface of a road that is the result of the cyclical forces applied to broken pavement by traffic, causing shattered pieces of pavement to be ...