Deep Learning for Crack-Like Object Detection
Häftad, Engelska, 2024
Av Kaige Zhang, Heng-Da Cheng, Heng-Da (Utha State Uni.) Cheng
339 kr
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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.
Produktinformation
- Utgivningsdatum2024-10-09
- Mått138 x 216 x 6 mm
- Vikt145 g
- FormatHäftad
- SpråkEngelska
- Antal sidor100
- FörlagTaylor & Francis Ltd
- ISBN9781032181196