지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.18 No.2
- 발행연도
- 2018.6
- 수록면
- 126 - 134 (9page)
- DOI
- 10.5391/IJFIS.2018.18.2.126
이용수
초록· 키워드
오류제보하기
Recognizing handwritten digits was challenging task in a couple of years ago. Thanks to machine learning algorithms, today, the issue has solved but those algorithms require much time to train and to recognize digits. Thus, using one of those algorithms to an application that works in real-time, is complex. Notwithstanding use of a trained model, if the model uses deep neural networks it requires much more time to make a prediction and becomes more complicated as well as memory usage also increases. It leads real-time application to delay and to work slowly even using trained model. A memory usage is also essential as using smaller memory of trained models works considerable faster comparing to models with huge pre-processed memory. For this work, we implemented four models on the basis of unlike algorithms which are capsule network, deep residual learning model, convolutional neural network and multinomial logistic regression to recognize handwritten digits. These models have unlike structure and they have showed a great results on MNIST before so we aim to compare them in real-time environment. The dataset MNIST seems most suitable for this work since it is popular in the field and basically used in many state-of-the-art algorithms beyond those models mentioned above. We purpose revealing most suitable algorithm to recognize handwritten digits in real-time environment. Also, we give comparisons of train and evaluation time, memory usage and other essential indexes of all four models.
목차
Abstract
1. Introduction
2. Related Works
3. Methods
4. Experiments
5. Conclusion
References
참고문헌 (34)
참고문헌 신청
[학술지(정기간행물)] - 김광일 / 2018 / Context-Aware Information Provisioning for Vessel Traffic Service Using Rule-Based and Deep Learning Techniques / International Journal of Fuzzy Logic and Intelligent systems 18 (1) : 13 ~ 19
[학술지(정기간행물)] - 이혜우 / 2017 / Deep Neural Network Self-training Based on Unsupervised Learning and Dropout / International Journal of Fuzzy Logic and Intelligent systems 17 (1) : 1 ~ 9
[단행본] - W. A. Bergerud / 1996 / Introduction to regression models: with worked forestry examples
[학술지(정기간행물)] - S. Sabour / 2017 / Dynamic routing between capsules / Advances in Neural Information Processing Systems 30 : 3859 ~ 3869
[학술지(정기간행물)] - A. Alsaafin / 2017 / A minimal subset of features using feature selection for handwritten digit recognition / Journal of Intelligent Learning Systems and Applications 9 (4) : 55 ~ 68
[학술지(정기간행물)] - 이혜우 / 2017 / Deep Neural Network Self-training Based on Unsupervised Learning and Dropout / International Journal of Fuzzy Logic and Intelligent systems 17 (1) : 1 ~ 9
[단행본] - W. A. Bergerud / 1996 / Introduction to regression models: with worked forestry examples
[학술지(정기간행물)] - S. Sabour / 2017 / Dynamic routing between capsules / Advances in Neural Information Processing Systems 30 : 3859 ~ 3869
[학술지(정기간행물)] - A. Alsaafin / 2017 / A minimal subset of features using feature selection for handwritten digit recognition / Journal of Intelligent Learning Systems and Applications 9 (4) : 55 ~ 68
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UCI(KEPA) : I410-ECN-0101-2018-003-002236851