Camouflage object detection (COD) aims to identify objects that blend seamlessly into complex backgrounds, making it inherently more challenging than conventional object detection. However, most ...

Abstract: Object detection for waste management is limited by the scarcity of large, labeled real-world datasets. To overcome this, we developed a synthetic dataset generation method that enhances ...

Turnitin has expanded its AI writing detection capabilities with AI bypasser detection, a feature designed to help identify text that has been modified by AI humanizer tools. "Humanizers," which ...

Facing 10 wild prisoners with nothing but stealth on my side, I went full camo to stay alive. Think hide-and-seek meets prison break—but with way more adrenaline. Business jet that crashed in Michigan ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...

According to a statement emailed to The Debrief and a separate story on the organization’s website, when Dr. John Sandusky first joined Sandia almost 20 years ago, he was asked if the heliostats at ...

Small object detection is a critical task in applications like autonomous driving and ship black smoke detection. While Deformable DETR has advanced small object detection, it faces limitations due to ...

One of the biggest issues with large language models (LLMs) is working with your own data. They may have been trained on terabytes of text from across the internet, but that only provides them with a ...

This project implements real-time object detection using OpenCV and a pre-trained SSD MobileNet V3 model. The application can identify and label various objects from a webcam feed or uploaded images ...