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 ...

Timely and accurate detection of foreign objects is crucial for the safe operation of transmission lines in power grid. Currently, object detection models have more and more parameters and their ...

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 ...

Wildfires pose a severe threat to ecosystems, economies, and human lives, exemplified by the 2019 Australian bushfires, which devastated 46 million acres, destroyed thousands of structures, and caused ...

Over one million people in the U.S. have Parkinson’s disease (PD), a number that is expected to rise to 1.2 million by 2030. This condition affects more than 10 million people globally, with ...

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.

For this tutorial, we will load an image in color and convert it to the RGB format so it can be displayed correctly using matplotlib. import cv2 import numpy as np import matplotlib.pyplot as plt from ...

Convolution filters are a fundamental building block in image processing and computer vision. They are used to extract specific features from an image by applying a small matrix of numbers, called the ...

ARC Centre of Excellence for Transformative Meta-Optical Systems (TMOS), Research School of Physics, The Australian National University, Canberra, ACT 2601, Australia ARC Centre of Excellence for ...

Functional near-infrared spectroscopy (fNIRS)-based mental workload (MWL) classification using machine learning (ML) and deep learning (DL) algorithms. Data acquisition through fNIRS system ...