Technical Name Automatic Multi-Pill Detection and Recognition System based on RetinaNet and Inception-ResNet
Project Operator Tajen University/National Cheng Kung University
Summary
The pills detection system is built based on the Feature Pyramid Network and Convolution Normal Network (CNN). Two-stage CNN architecture is used for pills localization and pill classification. The accuracy and execution time of the pill detection are 90% and 0.02s, respectively.
Scientific Breakthrough
本技術特點:
1.結合特徵金字塔物件偵測技術與蒐集不同藥丸擺放位置,可快速於輸入影像中,精準偵測不同擺放位置一至多顆藥丸。
2.結合卷積辨識神經網路與蒐集不同平面旋轉角度的藥丸圖片,可對每顆不同旋轉角度的藥丸進行快速且精準的辨識。
Industrial Applicability
The pill detection can be applied to wide range of situations, such as home medicine safety, understand the unknown drug. Medical personnel and patients often have difficulties in distinguishing unpackaged pills. The improvement in medication knowledge and the provision of adequate pill information to patients have become important issues in an effort to increase medicine safety.
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