In railway surface defect detection applications, supervised deep learning methods suffer from the problems of insufficient samples and an imbalance between positive negative samples. To overcome these problems, we propose a lightweight two-stage architecture including cropping network (RC-Net) defects removal variational autoencoder (DR-VAE), which requires only normal for training to achieve ...

Surface defect detection is an extremely crucial step to ensure the quality of industrial products. Nowadays, convolutional neural networks (CNNs) based on encoder–decoder architecture have achieved tremendous success in various tasks. However, intrinsic locality convolution prevents them from modeling long-range interactions explicitly, making it difficult distinguish pseudo-defects cluttered ...

The rising quality and throughput demands of the manufacturing domain require flexible, accurate explainable computer-vision solutions for defect detection. Deep Neural Networks (DNNs) reach state-of-the-art performance on various tasks but wide-spread application in industrial is blocked by lacking explainability DNN decisions. A promising, human-readable solution given saliency maps, heatmaps...

Fabric defect is one of the most important and serious matters quality control in textile industry Bangladesh. This task takes a lot time money. For this reason we have introduced simple process to find defects on fabric based edge detection. mainly focused image processing which can be integrated with detection automation system. In paper tried new approach using filter method found good resul...

various indexes such as rvi, ndvi, savi and osavi have been proposed for vegetation detection using satellite images. these indexes have been obtained based on high reflectance of the vegetation in near infrared band and its high absorption in red band. basic defect of these indexes are using them in various regions without any changes in index structure. in other words, these indexes have not ...

Pavement disease detection is an important task for ensuring road safety. Manual visual requires a significant amount of time and effort. Therefore, automated identification technique required to guarantee that city tasks are performed. However, due the irregular shape large-scale differences in diseases, as well imbalance between foreground background, challenging. Because this, we created dee...