869 citations · 1.2k across the 2 of their papers we have counts for
5 papers
Mixed supervision for surface-defect detection: from weakly to fully supervised learning
Jakob Božič, Domen Tabernik, Danijel Skočaj
Deep-learning methods have recently started being employed for addressing surface-defect detection problems in industrial quality control. However, with a large amount of data need…
End-to-end training of a two-stage neural network for defect detection
Jakob Božič, Domen Tabernik, Danijel Skočaj
Segmentation-based, two-stage neural network has shown excellent results in the surface defect detection, enabling the network to learn from a relatively small number of samples. I…
Deep Learning for Large-Scale Traffic-Sign Detection and Recognition
Domen Tabernik, Danijel Skočaj
Automatic detection and recognition of traffic signs plays a crucial role in management of the traffic-sign inventory. It provides accurate and timely way to manage traffic-sign in…
Segmentation-Based Deep-Learning Approach for Surface-Defect Detection
Domen Tabernik, Samo Šela, Jure Skvarč +1
Automated surface-anomaly detection using machine learning has become an interesting and promising area of research, with a very high and direct impact on the application domain of…
Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks
Domen Tabernik, Matej Kristan, Aleš Leonardis
Convolutional neural networks excel in a number of computer vision tasks. One of their most crucial architectural elements is the effective receptive field size, that has to be man…