Detection of a casting defect tracked by deep convolution neural network

Author:

Lin Jinhua,Yao Yu,Ma Lin,Wang Yanjie

Funder

National High-tech R&D Program

Science and Technology Project of the thirteenth Five-Year Plan

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Reference28 articles.

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2. Huang Q, Wu Y, Baruch J, Jiang P, Peng Y (2009) A template model for defect simulation for evaluating nondestructive testing in X-radiography. IEEE Trans Syst Man Cybern Syst Hum 39(2):466–475

3. Anand RS, Kumar P (2009) Flaw detection in radiographic weldment images using morphological watershed segmentation technique. Ndt & E Int 42(1):2–8

4. Dubey S, Shah K (2012) Analysis of various flaws detection using segmentation techniques in weld images. Int J Adv Eng Technol 3(2):765–774

5. Manjula K, Vijayarekh K, Venkatrama B (2014) Weld flaw detection using various ultrasonic techniques: a review. J Appl Sci 14(14):1529–1535

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