Methods: This paper proposes IYFVMNet, an improved lightweight detection network based on YOLOv8. The key challenges include ... which increases the difficulty of object detection. (2) Data imbalance.

One of the newer methods they are using involves targeting USB flash drives. It may seem surprising that they would focus on something as simple as a flash drive, but the data it holds can be ...

This repository contains the first version of an object detection system developed for a UAV (Unmanned Aerial Vehicle) project during an internship. The system is built using YOLOv8 and a ...

The Brain Tumor Detector is an easy-to-use, high-accuracy application designed to aid in the early detection of brain tumors. By utilizing YOLOv8 for real-time object detection and Streamlit for an ...

It also focuses on hard samples to reduce the impact of easily misclassified samples, thereby enhancing the model’s performance in complex fire detection. We tested our method on the D-Fire dataset.

[5] talks about using ... When data is transferred from Clk1 to Clk2 domain at clock edge X, there is a possibility of glitch which cannot be seen in functional simulation, but will appear in the ...

Traditional manual inspection methods are inefficient and costly, while deep learning-based object detection algorithms often ... RACycle-GAN) and Damage Detection Enhanced YOLOv8 (DDE-YOLOv8), this ...