A hierarchical training-convolutional neural network with feature alignment for steel surface defect recognition
Steel is a basic material, and vision-based defect recognition is important for quality.
Recently, deep learning, especially convolutional neural network (CNN), has become a …
Recently, deep learning, especially convolutional neural network (CNN), has become a …
Deep ensemble transfer learning-based approach for classifying hot-rolled steel strips surface defects
Over the last few years, advanced deep learning-based computer vision algorithms are
revolutionizing the manufacturing field. Thus, several industry-related hard problems can be …
revolutionizing the manufacturing field. Thus, several industry-related hard problems can be …
Strip steel surface defects classification based on generative adversarial network and attention mechanism
Z Hao, Z Li, F Ren, S Lv, H Ni - Metals, 2022 - mdpi.com
In a complex industrial environment, it is difficult to obtain hot rolled strip steel surface defect
images. Moreover, there is a lack of effective identification methods. In response to this, this …
images. Moreover, there is a lack of effective identification methods. In response to this, this …
Moving towards agriculture 4.0: An AI-AOI carrot inspection system with accurate geometric properties
This paper aims to give a new impetus to the development of automated inspection systems
in the food industry, specifically by examining the geometric properties of agricultural …
in the food industry, specifically by examining the geometric properties of agricultural …
Surface defect classification of hot-rolled steel strip based on mixed attention mechanism
H Fan, Q Dong, N Guo - Robotic Intelligence and Automation, 2023 - emerald.com
Purpose This paper aims to propose a classification method for steel strip surface defects
based on a mixed attention mechanism to achieve fast and accurate classification …
based on a mixed attention mechanism to achieve fast and accurate classification …
A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing.
T Hussain, J Hong, J Seok - Computers, Materials & …, 2024 - search.ebscohost.com
Smart manufacturing is a process that optimizes factory performance and production quality
by utilizing various technologies including the Internet of Things (IoT) and artificial …
by utilizing various technologies including the Internet of Things (IoT) and artificial …
Relational-based transfer learning for automatic optical inspection based on domain discrepancy
EIV Salgado, H Yan, Y Hong, P Zhu… - Optoelectronic …, 2023 - spiedigitallibrary.org
Transfer learning is a promising method for AOI applications since it can significantly shorten
sample collection time and improve efficiency in today's smart manufacturing. However …
sample collection time and improve efficiency in today's smart manufacturing. However …
Model-based Transfer Learning for Automatic Optical Inspection based on domain discrepancy
EIV Salgado, H Yan, Y Hong, P Zhu, S Zhu… - arXiv preprint arXiv …, 2023 - arxiv.org
Transfer learning is a promising method for AOI applications since it can significantly shorten
sample collection time and improve efficiency in today's smart manufacturing. However …
sample collection time and improve efficiency in today's smart manufacturing. However …
New Class Discovery of Steel Surface Defects Using Multi-View Self-Labeling and Overclustering
S Yao, L Yao, S Ren, X Ma, Q Kang… - … on Networking, Sensing …, 2024 - ieeexplore.ieee.org
In this paper, we study the problem of discovering new types of defects on steel surfaces.
Steel is an indispensable and important material in modern industry, making steel surface …
Steel is an indispensable and important material in modern industry, making steel surface …