An End-to-End Steel Surface Defect Detection Approach via Fusing Multiple Hierarchical Features
Northeastern University · Loughborough University
Abstract
A complete defect detection task aims to achieve the specific class and precise location of each defect in an image, which makes it still challenging for applying this task in practice. The defect detection is a composite task of classification and location, leading to related methods is often hard to take into account the accuracy of both. The implementation of defect detection depends on a special detection data set that contains expensive manual annotations. In this paper, we proposed a novel defect detection system based on deep learning and focused on a practical industrial application: steel plate defect inspection. In order to achieve strong classification ability, this system employs a baseline…
Citation impact
- FWCI
- 75.56
- Percentile
- 100%
- References
- 52
Authors
4Topics & keywords
- Computer science
- Artificial intelligence
- Pattern recognition (psychology)
- Convolutional neural network
- Classifier (UML)
- Feature extraction
- Minimum bounding box
- Bounding overwatch
- Industry, innovation and infrastructure