An Improved YOLOP Lane-Line Detection Utilizing Feature Shift Aggregation for Intelligent Agricultural Machinery

An Improved YOLOP Lane-Line Detection Utilizing Feature Shift Aggregation for Intelligent Agricultural Machinery

Agricultural factories utilize advanced facilities and technologies to cultivate crops in a controlled environment, enhancing operational yields and reducing reliance on natural resources. This is crucial for ensuring a stable supply of agricultural products year-round and plays a significant role i...

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Bibliographic Details
Main Authors: Cundeng Wang, Xiyuan Chen, Zhiyuan Jiao, Shuang Song, Zhen Ma
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Agriculture
Subjects:
agricultural factories
automated guided vehicles (AGVs)
multi-task learning (MTL)
changeable agricultural factory scenarios
MTNet
lane-line detection
Online Access:https://www.mdpi.com/2077-0472/15/13/1361
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