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| Full Title | Deep Learning for Crack-Like Object Detection 1st Edition |
|---|---|
| Author(s) | Kaige Zhang, Heng-Da Cheng |
| Edition | 1st Edition |
| ISBN | 9781000871319, 9781032181189, 9781032181196, 9781003252948, 9781000871272 |
| Publisher | CRC Press |
| Format | PDF and EPUB |
Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems. This book discusses crack-like object detection problem comprehensively. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. It provides a detailed review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.
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