Vision-Based Defect Detection for Mobile Phone Cover Glass using Deep Neural Networks
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Vision-Based Defect Detection for Mobile Phone Cover Glass using Deep Neural Networks' 의 참고문헌
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Weaklyand Semi-Supervised Learning of a DCNN for Semantic Image Segmentation
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Transfer Learning by Ranking for Weakly Supervised Object Annotation
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Touch Screen Defect Inspection Based on Sparse Representation in Low Resolution Images,
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Signal Recovery from Random Measurements via Orthogonal Matching Pursuit
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Semi-Supervised and Unsupervised Extreme Learning Machines
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Semi-Supervised Learning with Deep Generative Models
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Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
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Semantic Segmentation Using Adversarial Networks
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Self-Taught Learning: Transfer Learning from Unlabeled Data
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Preliminary Research of Surface Defect Recognition Based on Machine Vision
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Multi-Scale Context Aggregation by Dilated Convolutions
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Learning a Driving Simulator
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Learning Defect Classifiers for Textured Surfaces Using Neural Networks and Statistical Feature Representations,
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Learning Deconvolution Network for Semantic Segmentation
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International Workshop on Image Processing: Real-Time Edge and Motion Detection/Estimation
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Interacting with Paper on the Digitaldesk
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Imbalanced Defect Classification for Mobile Phone Screen Glass Using Multifractal Features and a New Sampling Method,
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Generative Adversarial Nets
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Fully Convolutional Networks for Semantic Segmentation
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Development of an Automated Optical Inspection System for Mobile Phone Panels
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Development of Detection Techniques of Surface Defects for Large Aperture Optical Elements Based on Machine Vision
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Defect Inspection and Extraction of the Mobile Phone Cover Glass Based on the Principal Components Analysis
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Deep Convolutional Neural Networks for Detection of Rail Surface Defects
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Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures
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Automatic Surface Defect Detection for Mobile Phone Screen Glass Based on Machine Vision
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Automatic Detection of Surface Defects on Rolled Steel Using Computer Vision and Artificial Neural Networks
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Automatic Defect Detection on Hot-Rolled Flat Steel Products
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An Automatic Wafer Inspection System Using Pipelined Image Processing Techniques
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A threshold selection method from gray level histograms
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A Survey on Transfer Learning
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A Generic Deep-Learning-Based Approach for Automated Surface Inspection
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3D Shape Induction from 2D Views of Multiple Objects
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Vision-Based Defect Detection for Mobile Phone Cover Glass using Deep Neural Networks'
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