Classification of scanning electron microscope images of pharmaceutical excipients using deep convolutional neural networks with transfer learning

Classification of scanning electron microscope images of pharmaceutical excipients using deep convolutional neural networks with transfer learning

Convolutional Neural Networks (CNNs) are image analysis techniques that have been applied to image classification in various fields. In this study, we applied a CNN to classify scanning electron microscopy (SEM) images of pharmaceutical raw material powders to determine if a CNN can evaluate particl...

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Bibliographic Details
Main Authors: Hiroaki Iwata, Yoshihiro Hayashi, Aki Hasegawa, Kei Terayama, Yasushi Okuno
Format: Article
Language:English
Published: Elsevier 2022-12-01
Series:International Journal of Pharmaceutics: X
Subjects:
Convolutional neural networks
Machine learning
Scanning electron microscope
Excipients
Powder
Artificial intelligence
Online Access:http://www.sciencedirect.com/science/article/pii/S259015672200024X

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http://www.sciencedirect.com/science/article/pii/S259015672200024X

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