Build a traffic light object detection project based on YOLOv5. At present, the average traffic light detection accuracy based on YOLOv5s is mAP_0 = 0.93919, mAP_0: 0.95 = 0.63967, which bas
Developing a system for field weed identification is crucial to improve agricultural operational efficiency and crop yield. This article elaborates on how to apply deep learning technology to develop
This blog post details how to use deep learning to build an advanced transmission line equipment inspection system. The system also integrates a user-friendly interface based on PySide6, which makes
This blog post describes the process of building a traffic sign recognition system using deep learning in detail, and provides the complete implementation code. The system uses the advanced YOLOv8 alg
The system uses PySide6 as a GUI library to provide an intuitive and user-friendly interface. Below, I will introduce the functions and design of each main interface in detail. (1) The system provide
The system can accurately identify and distinguish different paddy pest types. It supports detection through pictures, picture sets, video files, and real-time cameras. Features include columnar graph
this project will develop an C++ and Python and Android version of the license plate detection and recognition APP, wherein the license plate detection algorithm using YOLOv5 model, license plate rec
The project is based on the Pytorch deep learning framework and the implementation of the hand keypoint detection (hand pose estimation) model, in which the hand detection adopts the YOLOv5 model, and
With the development of the global economy, the scale of the fruit consumption market continues to expand, and the types of fruits are increasingly abundant. Fruit detection and identification technol
This project will use deep learning method to build a training and testing system for fruit classification recognition, and implement a simple fruit image classification recognition system. At present