An Efficient MLP-Based Point-Guided Segmentation Network for Ore Images With Ambiguous Boundary-Reference-Cited by-同舟云学术

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An Efficient MLP-Based Point-Guided Segmentation Network for Ore Images With Ambiguous Boundary

Published:2024-07 Issue:7 Volume:20 Page:9152-9162
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Sun Guodong¹^ORCID,Peng Yuting¹^ORCID,Cheng Le¹^ORCID,Xu Mengya²^ORCID,Wang An³^ORCID,Wu Bo⁴^ORCID,Ren Hongliang²^ORCID,Zhang Yang¹^ORCID

Affiliation:

1. School of Mechanical Engineering, Hubei University of Technology, Wuhan, China

2. Department of Biomedical Engineering, National University of Singapore (NUS), Singapore

3. Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China

4. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China

Funder

National Natural Science Foundation of China

State Key Laboratory of Novel Software Technology

State Key Laboratory of Intelligent Optimized Manufacturing in Mining and Metallurgy Process

Beijing Key Laboratory of Process Automation in Mining and Metallurgy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9424/10582275/10495720.pdf?arnumber=10495720

Reference40 articles.

1. Visual Fault Detection of Multi-Scale Key Components in Freight Trains

2. A Boundary Consistency-Aware Multitask Learning Framework for Joint Activity Segmentation and Recognition With Wearable Sensors

3. A Unified Light Framework for Real-Time Fault Detection of Freight Train Images

4. Object Detection Based on Multi-Layer Convolution Feature Fusion and Online Hard Example Mining

5. Feature disentanglement in one-stage object detection

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