Learn about the methodology and tools for AI-driven arc fault detection to create real-time classification on MCUs, improving accuracy and reducing false trips, for edge deployment. Learn how embedded ...

At present, in the field of cherry recognition, problems such as dense fruit growth and frequent occlusions of branches and leaves affect the accuracy of the recognition process. To address these ...

The core file description is as follows: We have provided the complete implementation codes of three core innovative modules of GDD-YOLO, which are the key to optimizing the accuracy and computational ...

This research presents a Driver Drowsiness Detection System (DDDS) that uses a Convolutional Neural Network (CNN) to improve road safety. The system uses a vast dataset of 97,860 images from the ...

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.

We introduce YOGA, a deep learning based yet lightweight object detection model that can operate on low-end edge devices while still achieving competitive accuracy. The YOGA architecture consists of a ...