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portada Deep Learning for Crack-Like Object Detection
Type
Physical Book
Author
Publisher
Language
English
Pages
100
Format
Hardcover
Dimensions
21.6 x 14.0 x 0.8 cm
Weight
0.27 kg.
ISBN13
9781032181189
Edition No.
1
Categories

Deep Learning for Crack-Like Object Detection

Kaige Zhang (Author) · Heng-Da Cheng (Author) · CRC Press · Hardcover

Deep Learning for Crack-Like Object Detection - Zhang, Kaige ; Cheng, Heng-Da

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Synopsis "Deep Learning for Crack-Like Object Detection "

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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