This becomes a major problem for fault detection, where the targets appear very small on the images and vary in both types and sizes. In this paper we propose a ...

This paper proposes a new network architecture, DefectNet, that offers multi-class defect detection on highly-imbalanced datasets and proposes a hybrid loss ...

This becomes a major problem for fault detection, where the targets appear very small on the images and vary in both types and sizes. In this paper we propose a ...

In this paper we pro- pose a new network architecture, DefectNet, that offers multi- class (including but not limited to) defect detection on highly- imbalanced ...

Defectnet: Multi-Class Fault Detection on Highly-Imbalanced Datasets ... detecting various defect size on a highly imbalanced dataset. The proposed DefectNet ...

GPL-3.0 license. Defectnet: Multi-Class Fault Detection on Highly-Imbalanced Datasets Paper: https://arxiv.org/abs/1904.00863. For training the model ...

Sep 25, 2021 · In this paper, we propose a new network, DefectNet, for detecting various defect size on a highly imbalanced dataset. The proposed DefectNet, ...

Our new dataset enables us to formulate the problem as a multi-task ... DefectNET: multi-class fault detection on highly-imbalanced datasets · pui ...

DefectNET: multi-class fault detection on highly-imbalanced datasets ... As a data-driven method, the performance of deep convolutional neural networks (CNN) ...

Missing: DefectNET: fault detection