Abstract: The development of a real-time railway obstacle detection framework based on an optimized YOLO network to ensure increased safety and operational efficiency by accurate identification of ...

What if a device could see the world the same way humans do, seeing objects, recognizing them, and understanding what they are in real time? Just like our eyes capture visuals and our brain instantly ...

In response to the challenges of small object detection in UAV aerial photography, such as complex backgrounds, tiny targets, dense targets, and edge deployment, the YOLOv11n model was improved.

Abstract: In the present research work, a system is developed that can detect objects in real-time using a combination of the ESP32 CAM module and Python programming. The goal was to show how ...

With the development of bionic computer vision for images processing, researchers have easily obtained high-resolution zoom sensing images. The development of drones equipped with high-definition ...

YOLO, meaning 'You Only Look Once', is a popular model for real-time object detection. The YOLO algorithm divides images into a grid, with each cell responsible for detecting objects. YOLOv1, ...

Detection on youtube livestream walk in Tokyo, Japan. This package contains two modules that perform real-time object detection from Youtube video stream. A possible use case is detection with a drone ...

All prior detection systems repurpose classifiers or localizers to perform detection. They apply the model to an image at multiple locations and scales. High scoring regions of the image are ...