Researchers at the University of Tsukuba have developed the SPADE (Simulator-assisted PerformAbility Design methodology for UAV-based Systems) approach for accurate quality assessments of uncrewed ...

This letter presents the development of a real-time object detection system using frequency modulated continuous wave millimeter-wave (mmWave) radar signals and the python productivity for zynq ...

Object detection is a foundation process in computer vision having widespread applications in autonomous driving, medical diagnostics and security monitoring. Recent advancements and development in ...

The Raspberry Pi 5 excels in simplicity and real-time object detection with minimal latency, while the Jetson Orin Nano Super supports customizable detection and advanced use cases.

This project is a real-time object detection system that leverages the YOLOv5 model for detecting objects in a video stream from a webcam or other video input. The system is built using a Flask web ...

The software is YOLO v7, a state-of-the-art real-time object detection model presently used for autonomous driving, surveillance, and robotics. The workflow and parametrization needed for building a ...

TL;DR Key Takeaways : The Raspberry Pi AI HAT, combined with YOLO models, enables real-time object detection, counting, and positional tracking for applications like security and automation.

The Need for Better Efficiency Many applications require object detection to run in real-time on devices with limited compute resources. As models become larger and more computationally intensive, ...