[HTML][HTML] Superpixel-Based Graph Convolutional Network for UAV Forest Fire Image Segmentation

Y Mu, L Ou, W Chen, T Liu, D Gao - Drones, 2024 - mdpi.com
Given the escalating frequency and severity of global forest fires, it is imperative to develop
advanced detection and segmentation technologies to mitigate their impact. To address the …

[HTML][HTML] Large Span Sizes and Irregular Shapes Target Detection Methods Using Variable Convolution-Improved YOLOv8

Y Gao, W Liu, HC Chui, X Chen - Sensors, 2024 - mdpi.com
In this work, an object detection method using variable convolution-improved YOLOv8 is
proposed to solve the problem of low accuracy and low efficiency in detecting spanning and …

[HTML][HTML] An image-based fire monitoring algorithm resistant to fire-like objects

F Xu, X Zhang, T Deng, W Xu - Fire, 2023 - mdpi.com
Due to its wide monitoring range and low cost, visual-based fire detection technology is
commonly used for fire detection in open spaces. However, traditional fire detection …

改进YOLOv5 的探地雷达常见地下管线识别

王惠琴, 罗佳, 何永强, 曹明华, 高大庆, 李佳豪 - 地球物理学报, 2024 - dzkx.org
针对当前探地雷达(Ground Penetrating Radar, GPR) 图像识别准确率低, 且小目标识别困难等
问题, 本文将YOLOv5 (You Only Look Once) 和ConvNeXt 网络相结合, 提出了一种适用于GPR …

[HTML][HTML] Vegetation Classification and a Biomass Inversion Model for Wildfires in Chongli Based on Remote Sensing Data

F Xu, W Chen, R Xie, Y Wu, D Jiang - Fire, 2024 - mdpi.com
Vegetation classification, biomass assessment, and wildfire dynamics are interconnected
wildfire-ecosystem components. The Chongli District, located in Zhangjiakou City, was the …

Identification of common underground pipelines by ground penetrating radar based on improved YOLOv5

HQ WANG, J LUO, YQ HE, MH CAO… - Chinese Journal of …, 2024 - en.dzkx.org
Aiming at the current problems of low accuracy of ground-penetrating radar image
recognition and difficulty in recognizing small targets, this paper combines YOLOv5 and …