Zobrazeno 1 - 10 of 73 pro vyhledávání: '"Masaki Kurematsu"'
2
Multi-Task Learning for Scene Text Image Super-Resolution with Multiple Transformers
Autor: Kosuke Honda, Masaki Kurematsu, Hamido Fujita, Ali Selamat
Publikováno v: Electronics; Volume 11; Issue 22; Pages: 3813
Scene text image super-resolution aims to improve readability by recovering text shapes from low-resolution degraded text images. Although recent developments in deep learning have greatly improved super-resolution (SR) techniques, recovering text im
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab06a69caac22d3982cc0847c0381d38
Zobrazit plný text záznamu
3
A Study on an Imbalanced Data Processing Method with Maharanobis-Taguchi System
Autor: Masaki Kurematsu
Imbalance data processing is one of big issues for machine learning. There are some proposed approaches. On the other hand, Maharanobis-Taguchi System (MTS) is a well-known approach in quality engineering. Although the target of both researches are s
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::64a530abb8d1f586fff987a651242938
https://doi.org/10.3233/faia220298
Zobrazit plný text záznamu
6
A Study of a Patent Documents Classification System Using Rough Set Theory and Machine Translation
Autor: Masaki Kurematsu
Publikováno v: SoMeT
We should check whether there are any existing patent documents whose claims fall foul of our idea or innovation before we submit own idea or innovation as a patent. We need a lot of resource to do it, because there are a lot of existing patent docum
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::11cb2988084e484c911604bfad7f76d3
https://doi.org/10.3233/faia200583
Zobrazit plný text záznamu
7
Elektronická kniha
Trends in Applied Knowledge-Based Systems and Data Science : 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Morioka, Japan, August 2-4, 2016, Proceedings
Autor: Hamido Fujita, Moonis Ali, Ali Selamat, Jun Sasaki, Masaki Kurematsu
This book constitutes the refereed conference proceedings of the 29th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, held in Morioka, Japan, in August 2-4, 2016. The 80 revised
Zobrazit plný text záznamu
9
A Framework for a Decision Tree Learning Algorithm with Rough Set Theory
Autor: Hamido Fujita, Jun Hakura, Masaki Kurematsu
Publikováno v: Communications in Computer and Information Science ISBN: 9783319226880
SoMeT
In this paper, we improve the conventional decision tree learning algorithm using rough set theory. First, our approach gets the upper approximate for each class. Next, it generates the decision tree from each upper approximate. Each decision tree sh
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7315a4670ff68b8f07c944a715bb2ad9
https://doi.org/10.1007/978-3-319-22689-7_26
Zobrazit plný text záznamu
10
A Framework for a Decision Tree Learning Algorithm with K-NN
Autor: Jun Hakura, Hamido Fujita, Masaki Kurematsu
Publikováno v: Communications in Computer and Information Science ISBN: 9783319175294
SoMeT (Selected Papers)
In this paper, we proposed a modified decision tree learning algorithm. We tried to improve the conventional decision tree learning algorithm. There are some approaches to do it. These methods have a modified learning phase and a decision tree made b
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2f68f2befc8996b46dfcc671f5d7bcf5
https://doi.org/10.1007/978-3-319-17530-0_4
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje