Ceramic tile surface defect detection based on deep learning

A Real-Time Apple Targets Detection Method for Picking Robot Based on Improved YOLOv5

(2021) Bin Yan et al.   Remote Sensing

Automated Control of Surface Defects on Ceramic Tiles Using 3D Image Analysis

(2020) Andrzej Sioma   Materials

Review of non-destructive testing methods for defect detection of ceramics

(2020) Zhike Zhao   CERAMICS INTERNATIONAL

An improved deep residual network with multiscale feature fusion for rotating machinery fault diagnosis

(2020) Feiyue Deng et al.   MEASUREMENT SCIENCE and TECHNOLOGY

A real-time detection approach for bridge cracks based on YOLOv4-FPM

(2020) Zhenwei Yu et al.   AUTOMATION IN CONSTRUCTION

Segmentation-based deep-learning approach for surface-defect detection

(2019) Domen Tabernik et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Detection of a casting defect tracked by deep convolution neural network

(2018) Jinhua Lin et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Real-time biscuit tile image segmentation method based on edge detection

(2018) Tomislav Matić et al.   ISA TRANSACTIONS

Literature review of Industry 4.0 and related technologies

(2018) Ercan Oztemel et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Automatic detection and classification of the ceramic tiles’ surface defects

(2017) Saeed Hosseinzadeh Hanzaei et al.   PATTERN RECOGNITION

Design of deep convolutional neural network architectures for automated feature extraction in industrial inspection

(2016) Daniel Weimer et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Region-Based Convolutional Networks for Accurate Object Detection and Segmentation

(2016) Ross Girshick et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Surface defect detection in tiling Industries using digital image processing methods: Analysis and evaluation

(2014) Mohammad H. Karimi et al.   ISA TRANSACTIONS