Acknowledgement
본 논문은 해양수산부 "해양 플라스틱 쓰레기 저감을 위한 기술개발"사업(20200584)의 연구과제로 수행되었음.
References
- H. S. Jang "Research on plastic regulation trends and innovation business models in major countries", Institute for international trand No.13 pp. 2093-3118, 2019.
- J. H. Choi, B. C. Jeon, M. W. Cho. " Development of Web Based Mold Discrimination System using the Matching Process for Vision Information and CAD DB" Transactions of the Korean Society of Machine Tool Engineers, Vol.15 No.5, pp 37-43 2006.
- H. Y. Bae, H. J. Kim, J. I. Paeng, H. S. Sim, S. H. Han, J. C. Moon " A Study on Shape Recognition Technology of Die Casting and Forging Parts Based on Robot Vision for Inspection Process Automation in Limit Environment" Journal of The Korean Society of Industry Convergence Vol.21, No.6 pp. 369-378 2018.
- M. Y. Cho1, M. S. Jang, C. S. Jang, D. H. Lee "Evaluation of Object Recognition Intelligence of Social Robots" 19th International Conference on Control, Automation and Systems, 2019.
- K. K. Kim, S. S. Kang, J. B. Kim, J. Y. Lee, H. M. Do, T. Y. Choi, J. H. Kyung " Object Recognition Method for Industrial Intelligent Robot" J. Korean Soc. Precis. Eng., Vol. 30, No. 9, pp. 901-908 2013. https://doi.org/10.7736/KSPE.2013.30.9.901
- Y. Bengio, A. Courville, P. Vincent, "Representation Learning: AReview and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol35, issue8, pp. 1798-1828. 2013. https://doi.org/10.1109/TPAMI.2013.50
- Y. Bengio, Y. LeCun, G. Hinton, "Deep Learning". Nature. Vol.521 pp. 436-444, 2015. https://doi.org/10.1038/nature14539
- L. Deng, D. Yu, "Deep Learning: Methods and Applications" Foundations and Trends in Signal Processing, Vol. 7, 2014.
- Y. LeCun, Y. Bengio, G. Hinton, "Deep learning". Nature. Vol. 521, pp. 436-444. 2015. https://doi.org/10.1038/nature14539
- J. Schmidhuber, J. "Deep Learning in Neural Networks: An Overview", Neural Networks. Vol. 61, pp. 85-117, 2015. https://doi.org/10.1016/j.neunet.2014.09.003
- Y. Bengio, A. Courville, P. Vincent, "Representation Learning: AReview and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, issue. 8, pp. 1798-1828. 2013. https://doi.org/10.1109/TPAMI.2013.50
- https://en.wikipedia.org/wiki/Deep_learning