An End-to-End Particle Gradation Detection Method for Earth–Rockfill Dams from Images Using an Enhanced YOLOv8-Seg Model

An End-to-End Particle Gradation Detection Method for Earth–Rockfill Dams from Images Using an Enhanced YOLOv8-Seg Model

Rockfill particle gradation significantly influences mechanical performance in earth–rockfill dam construction, yet on-site screening is often time-consuming, labor-intensive, and structurally invasive. This study proposes a rapid and non-destructive detection method using mobile-based photography a...

Full description

Saved in:
Bibliographic Details
Main Authors: Yu Tang, Shixiang Zhao, Hui Qin, Pan Ming, Tianxing Fang, Jinyuan Zeng
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Sensors
Subjects:
earth–rockfill dam
particle gradation detection (PGD)
image instance segmentation (IIS)
dual-attention mechanism
transfer learning
Online Access:https://www.mdpi.com/1424-8220/25/15/4797
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/25/15/4797

Similar Items