深度学习实现缺陷检测
小白学视觉
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2021-12-29 09:00
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1、A fast and robust convolutional neural network-based defect detection model in product quality control
由于使用分类方式,准确率较为高
由于滑窗遍历,速度慢
2、Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network(基于深度卷积网络的接触网支架紧固件缺陷自动检测)
3、Automatic Fabric Defect Detection with a Multi-Scale Convolutional Denoising Autoencoder Network Model(基于多尺度卷积消噪自编码网络模型的织物疵点自动检测)
4、An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces
5、Automatic Metallic Surface Defect Detection and Recognition with Convolutional Neural Networks
6、Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types
7、A Surface Defect Detection Method Based on Positive Samples
8、Segmentation-based deep-learning approach for surface-defect detection
9、SDD-CNN: Small Data-Driven Convolution Neural Networks for Subtle Roller Defect Inspection(小数据驱动卷积神经网络在轧辊微小缺陷检测中的应用)
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