$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

음각 정보를 이용한 딥러닝 기반의 알약 식별 알고리즘 연구
Pill Identification Algorithm Based on Deep Learning Using Imprinted Text Feature 원문보기

Journal of biomedical engineering research : the official journal of the Korean Society of Medical & Biological Engineering, v.43 no.6, 2022년, pp.441 - 447  

이선민 (가천대학교 간호대학 간호학과) ,  김영재 (가천대학교 의과대학 의공학교실) ,  김광기 (가천융합의과학원 융합의과학과)

Abstract ▼ AI-Helper 아이콘AI-Helper

In this paper, we propose a pill identification model using engraved text feature and image feature such as shape and color, and compare it with an identification model that does not use engraved text feature to verify the possibility of improving identification performance by improving recognition ...

주제어

#Pill identification   #Deep learning   #Imprinted text   #Keras OCR   #CNN  

표/그림 (6)

참고문헌 (31)

  1. Oh DE, Lee MS, Lee YD, Ye KN, and Kim JT. The reduction？of unreturned medication by improving the various medication return activities. Journal of Korean Society of Healthsystem Pharmacists. 2011;28(4):364-371. 

    상세보기 crossref

  2. Eoum GH, Lee JY, Cho YH, Cho YS, Hahn HJ, and Son IJ.？The Effect for Pharmacy Intervention on the Decrease of？Returned Medications from the Ward. Journal of Korean Society of Health-system Pharmacists. 2006;23(3):1-9. 

  3. Yi GY, Kim YJ, Kim ST, Kim HE, and Kim KG. Comparison and Verification of Deep Learning Models for Automatic？Recognition of Pills. Journal of Korea Multimedia Society.？2019;22(3):349-356. 

    원문보기 상세보기 crossref

  4. Wang Y, Ribera J, Liu C, Yarlagadda S, Zhu F. Pill Recognition Using Minimal Labeled Data. 2017 IEEE Third International Conference on Multimedia Big Data (BigMM). 2017;346-53. 

  5. Larios Delgado N, Usuyama N, Hall AK, Hazen RJ, Ma M,？Sahu S, et al. Fast and accurate medication identification.？NPJ digital medicine. 2019;2(1):1-9. 

    상세보기 crossref

  6. Ou YY, Tsai AC, Zhou XP, Wang JF. Automatic drug pills？detection based on enhanced feature pyramid network and？convolution neural networks. IET Computer Vision. 2020;14(1):9-17. 

    상세보기 crossref

  7. Suntronsuk S, Ratanotayanon S, editors. Automatic text imprint？analysis from pill images. 2017 9th International Conference？on Knowledge and Smart Technology (KST). 2017; 288-293. 

  8. Kim DW. Shape and Text Imprint Recognition of Pill Image？Taken with a Smartphone. Master's Thesis of Seoul National？University. 2017. 

  9. Ko DG. Optical Character Recognition Performance Comparison of CNNs and Tesseract. Master's Thesis of Sungkyunkwan University, 2016. [Online]. Available: http://www.riss.kr/link?idT14177015 

  10. Kim YJ and Kim KG. Development of an Optimized Deep？Learning Model for Medical Imaging. Journal of the Korean？Society of Radiology. 2020;81(6):1274-1289. 

  11. Hassanein A.S, Mohammad S, Sameer M, Ragab M.E. A？survey on Hough transform, theory, techniques and applications.？International Journal of Computer Science Issues (IJCSI).？2015;12(1):139-156. 

  12. Xu Z, Baojie X, Guoxin W. Canny edge detection based on？Open CV. 2017 13th IEEE international conference on electronic measurement & instruments (ICEMI), 2017;53-56. 

  13. Firoz R, Ali M.S, Khan M.N.U, Hossain M.K, Islam M.K,？Shahinuzzaman M. Medical image enhancement using morphological transformation. Journal of Data Analysis and Information Processing. 2016;4(1):1-12. 

    상세보기 crossref

  14. Erkan U, Gokrem L, Enginoglu S. Different applied median？filter in salt and pepper noise. Computers & Electrical Engineering, 2018;70:789-798. 

    상세보기 crossref

  15. Sahu S, Singh A.K, Ghrera S, Elhoseny M. An approach for？de-noising and contrast enhancement of retinal fundus image？using CLAHE. Optics & Laser Technology, 2019;110:87-98. 

    상세보기 crossref

  16. Baek Y, Lee B, Han D, Yun S, Lee H. Character region awareness for text detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019;9365-9374. 

  17. Lei Z, Zhao S, Song H, Shen J. Scene text recognition using？residual convolutional recurrent neural network. Machine？Vision and Applications. 2018;29(5):861-871. 

    상세보기

  18. Chotivatunyu P, Hnoohom N. Medicine Identification System？on Mobile Devices for the Elderly. 2020 15th International？Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). 2020;1-6. 

  19. Maitrichit N, Hnoohom N. Intelligent Medicine Identification System Using a Combination of Image Recognition and？Optical Character Recognition. 2020 15th International Joint？Symposium on Artificial Intelligence and Natural Language？Processing (iSAI-NLP). 2020;1-5. 

  20. Manaswi NK. Understanding and working with Keras. Deep Learning with Applications Using Python. Berkeley, CA:？Apress: 2018;31-43. 

  21. Chicho BT, Sallow AB. A Comprehensive Survey of Deep？Learning Models Based on Keras Framework. Journal of？Soft Computing and Data Mining. 2021;2(2):49-62. 

  22. Chollet F, Deep learning with Python. New York: Simon and？Schuster: 2021;62-64. 

  23. Gulli A, Kapoor A, Pal S. Deep learning with TensorFlow 2？and Keras: regression, ConvNets, GANs, RNNs, NLP, and more？with TensorFlow 2 and the Keras API. Birmingham, UK:？Packt Publishing Ltd: 2019;63-66. 

  24. Albawi S, Mohammed TA, Al-Zawi S. Understanding of a？convolutional neural network. 2017 international conference？on engineering and technology (ICET). 2017;1-6. 

  25. Sun M, Song Z, Jiang X, Pan J, Pang Y. Learning pooling for？convolutional neural network. Neurocomputing. 2017;224:96-104. 

    상세보기 crossref

  26. Vijayarani S, Janani R. Text mining: open source tokenization？tools-an analysis. Advanced Computational Intelligence: An？International Journal (ACII), 2016;3(1):37-47. 

    crossref

  27. Kudo T, Richardson J. Sentencepiece: A simple and language？independent subword tokenizer and detokenizer for neural text？processing. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018;66-71. 

  28. Dwarampudi M, Reddy N. Effects of padding on LSTMs and？CNNs. arXiv preprint arXiv:1903.07288, 2019. 

  29. Du C, Wang Y, Wang C, Shi C, Xiao B. Selective feature？connection mechanism: Concatenating multi-layer CNN features with a feature selector. Pattern Recognition Letters.？2020;129:108-14. 

    상세보기 crossref

  30. Ertam F, Aydin G. Data classification with deep learning using？Tensorflow. 2017 international conference on computer science and engineering (UBMK), 2017;755-758. 

  31. Yacouby R, Axman D. Probabilistic extension of precision,？recall, and F1 score for more thorough evaluation of classification models. Proceedings of the first workshop on evaluation and comparison of NLP systems. 2020;79-91. 

저자의 다른 논문 :

관련 콘텐츠

오픈액세스(OA) 유형

BRONZE

출판사/학술단체 등이 한시적으로 특별한 프로모션 또는 일정기간 경과 후 접근을 허용하여, 출판사/학술단체 등의 사이트에서 이용 가능한 논문

이 논문과 함께 이용한 콘텐츠

저작권 관리 안내
섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로