Pill Defect Detection Using an Improved Convolutional Neural Network-Reference-Cited by-同舟云学术

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Pill Defect Detection Using an Improved Convolutional Neural Network

Published:2022-07-14 Issue: Volume: Page:55-60
ISSN:2195-4356
Container-title:Lecture Notes in Mechanical Engineering
language:
Short-container-title:

Author:

Mac Thi Thoa^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-1540-6_7

Reference11 articles.

1. Tobore I et al (2019) Deep learning intervention for health care challenges: some biomedical domain considerations. JMIR Mhealth Uhealth 7(8):e11966 (2019)

2. Pillbox (2021). http://pillbox.nlm.nih.gov/pillimage/search.php. Accessed 9 Mar 2021

3. Pill Identifier (2021). http://reference.medscape.com/pill-identifier. Accessed 9 Mar 2021

4. Pill Identification Tool (2021). http://www.webmd.com/pill-identification. Accessed 9 Mar 2021

5. Guo Q, Zhang C, Liu H, Zhang X (2016) Defect detection in tire X-ray images using weighted texture dissimilarity. J Sens 2016

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1. Development of tablet defect detection model using biaxial planes discrete scanning algorithm;The International Journal of Advanced Manufacturing Technology;2023-08-14

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