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Journal Article Pill Detection Model for Medicine Inspection Based on Deep Learning
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Authors
Hyuk-Ju Kwon, Hwi-Gang Kim, Sung-Hak Lee
Issue Date
2022-01
Citation
Chemosensors, v.10, no.1, pp.1-17
ISSN
2227-9040
Publisher
MDPI
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.3390/chemosensors10010004
Abstract
This paper proposes a deep learning algorithm that can improve pill identification performance using limited training data. In general, when individual pills are detected in multiple pill images, the algorithm uses multiple pill images from the learning stage. However, when there is an increase in the number of pill types to be identified, the pill combinations in an image increase exponentially. To detect individual pills in an image that contains multiple pills, we first propose an effective database expansion method for a single pill. Then, the expanded training data are used to improve the detection performance. Our proposed method shows higher performance improvement than the existing algorithms despite the limited imaging and data set size. Our proposed method will help minimize problems, such as loss of productivity and human error, which occur while inspecting dispensed pills.
KSP Keywords
As loss, Data sets, Detection model, Higher performance, Human error, Identification performance, Learning Stage, Pill identification, deep learning(DL), deep learning algorithm, detection performance
This work is distributed under the term of Creative Commons License (CCL)
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CC BY