YOLOv5-RF: a deep learning method for tailings pond identification in high-resolution remote sensing images based on improved loss function

YOLOv5-RF: a deep learning method for tailings pond identification in high-resolution remote sensing images based on improved loss function

Tailings ponds are critical facilities in the mining industry, and accurate monitoring and management of these ponds are of paramount importance. However, conventional object detection methodologies, including recent advancements, often face significant challenges in addressing the complexities inhe...

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Bibliographic Details
Main Authors: Weiming Zhang, Wenliang Jiang, Qiang Li, Yi Luo, Heng Zhang, Qisong Jiao, Yongsheng Li, Hongbo Jiang
Format: Article
Language:English
Published: Taylor & Francis Group 2025-01-01
Series:Big Earth Data
Subjects:
Object detection
YOLOv5
loss function
tailings ponds
remote sensing identification
Online Access:https://www.tandfonline.com/doi/10.1080/20964471.2024.2436230
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https://www.tandfonline.com/doi/10.1080/20964471.2024.2436230

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