The Deep Learning Method for Image Segmentation to Improve the Efficiency of Data Processing Without Compromising the Accuracy of an Autonomous Driving Country-Road Pilot System After Image Classification

2021 ◽  
pp. 293-329
Author(s):  
Kathrin Kind-Trueller ◽  
Maria Psarrou ◽  
John Sapsford
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Data Processing ◽  
Image Classification ◽  
Autonomous Driving ◽  
Learning Method ◽  
Country Road

scholarly journals Fabric Defect Detection System Using Stacked Convolutional Denoising Auto-Encoders Trained with Synthetic Defect Data

2020 ◽  
Vol 10 (7) ◽  
pp. 2511
Author(s):  
Young-Joo Han ◽  
Ha-Jin Yu
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Machine Vision ◽  
Image Classification ◽  
Defect Detection ◽  
Detection System ◽  
Image Detection ◽  
Fabric Defect Detection ◽  
Fabric Defect ◽  
Segmentation Image

As defect detection using machine vision is diversifying and expanding, approaches using deep learning are increasing. Recently, there have been much research for detecting and classifying defects using image segmentation, image detection, and image classification. These methods are effective but require a large number of actual defect data. However, it is very difficult to get a large amount of actual defect data in industrial areas. To overcome this problem, we propose a method for defect detection using stacked convolutional autoencoders. The autoencoders we proposed are trained by using only non-defect data and synthetic defect data generated by using the characteristics of defect based on the knowledge of the experts. A key advantage of our approach is that actual defect data is not required, and we verified that the performance is comparable to the systems trained using real defect data.

SegFast-V2: Semantic image segmentation with less parameters in deep learning for autonomous driving

2019 ◽  
Vol 10 (11) ◽  
pp. 3145-3154 ◽  
Author(s):  
Swarnendu Ghosh ◽  
Anisha Pal ◽  
Shourya Jaiswal ◽  
K. C. Santosh ◽  
Nibaran Das ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Autonomous Driving ◽  
Semantic Image Segmentation
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