Ridge regression neural network for pediatric bone age assessment-Reference-Cited by-同舟云学术

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Ridge regression neural network for pediatric bone age assessment

Published:2021-05-08 Issue:20 Volume:80 Page:30461-30478
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Salim Ibrahim,Hamza A. Ben

Funder

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-021-10935-8.pdf

Reference31 articles.

1. Alshamrani K, Offiah A (2019) Applicability of two commonly used bone age assessment methods to twenty-first century UK children. Eur Radiol 1–10

2. Bengio Y (2009) Learning deep architectures for AI. Found Trends Mach Learn 2(1):1–127

3. Chattopadhay A, Sarkar A, Howlader P, Balasubramanian V (2018) Grad-CAM++: Generalized gradient-based visual explanations for deep convolutional networks. In: Proc. IEEE Winter conference on applications of computer vision

4. Chen X, Li J, Zhang Y, Lu Y, Liu S (2019) Automatic feature extraction in X-ray image based on deep learning approach for determination of bone age. Future Generation Computer Systems 1–7

5. Gilsanz V, Ratib O (2012) Hand bone age: A digital atlas of skeletal maturity. Springer, Berlin

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