Zerrendatu honen arabera: egilea "c9d6d132f33801620290080b1572987a"
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3D inspection methods for specular or partially specular surfaces
Maestro-Watson, Daniel (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2020)Deflectometric techniques are a powerful tool for the automated quality control of specular or shiny surfaces. These techniques are based on using a camera to observe a reference pattern reflected on the surface under ... -
Anomaly Detection and Automatic Labeling for Solar Cell Quality Inspection Based on Generative Adversarial Network
Balzategui, Julen; Eciolaza, Luka; Maestro-Watson, Daniel (MDPI, 2021)Quality inspection applications in industry are required to move towards a zero-defect manufacturing scenario, with non-destructive inspection and traceability of 100% of produced parts. Developing robust fault detection ... -
Deflectometric data segmentation for surface inspection: a fully convolutional neural network approach
Maestro-Watson, Daniel; Balzategui, Julen; Eciolaza, Luka; Arana-Arexolaleiba, Nestor (SPIE, 2020)The purpose of this paper is to explore the use of fully convolutional neural networks (FCN) to perform a semantic segmentation of deflectometric recordings for quality control of reflective surfaces. The proposed method ... -
Depth Data Denoising in Optical Laser Based Sensors for Metal Sheet Flatness Measurement: A Deep Learning Approach
Alonso, Marcos; Maestro-Watson, Daniel; Izaguirre Altuna, Alberto; andonegui, imanol (MDPI, 2021)Surface flatness assessment is necessary for quality control of metal sheets manufactured from steel coils by roll leveling and cutting. Mechanical-contact-based flatness sensors are being replaced by modern laser-based ...
