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A Machine Vision Case Study Of U-Net Networks For Superficial Corrosion And Dirt Image Segmentation On Industrial Coated Steel Structures

Product Number: 51322-17995-SG

Author: Wesley Kaizer, Otavio Correa

Publication Date: 2022

$20.00

Convolutional deep neural networks are one of the main machine learning techniques applied to computer vision and object recognition tasks. Currently, they are very popular due to their proven effectiveness in solving image classification tasks and their significant theoretical and practical importance to the advancement of the deep learning field. Examples of successful image classification networks developed are AlexNet, VGG, and GoogLeNet.^1,2,3

Products tagged with 'machine vision'

A Machine Vision Case Study Of U-Net Networks For Superficial Corrosion And Dirt Image Segmentation On Industrial Coated Steel Structures

Association for Materials Protection and Performance