Zobrazeno 1 - 10 of 386 pro vyhledávání: '"Masafumi HAGIWARA"'
1
Akademický článek
Cephalometric landmark detection without X-rays combining coordinate regression and heatmap regression
Autor: Kaisei Takahashi, Yui Shimamura, Chie Tachiki, Yasushi Nishii, Masafumi Hagiwara
Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract Fully automated techniques using convolutional neural networks for cephalometric landmark detection have recently advanced. However, all existing studies have adopted X-rays. The problem of direct exposure of patients to X-ray radiation rema
Externí odkaz: https://doaj.org/article/d94e0e0b9cfe4a7db3696bca812cb8af
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2
Akademický článek
Analogical Reasoning With Deep Learning-Based Symbolic Processing
Autor: Hiroshi Honda, Masafumi Hagiwara
Publikováno v: IEEE Access, Vol 9, Pp 121859-121870 (2021)
The authors propose analogical reasoning systems based on first-order predicate logic using deep learning. The proposed systems consist of a model combining recursive neural networks and Word2Vec. When unknown data is input in this trained model, sim
Externí odkaz: https://doaj.org/article/b7f1346f2301432688a96b6ebcdecf33
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3
Akademický článek
Question Answering Systems With Deep Learning-Based Symbolic Processing
Autor: Hiroshi Honda, Masafumi Hagiwara
Publikováno v: IEEE Access, Vol 7, Pp 152368-152378 (2019)
The authors propose methods to learn symbolic processing with deep learning and to build question answering systems by means of learned models. Symbolic processing, performed by the Prolog processing systems which execute unification, resolution, and
Externí odkaz: https://doaj.org/article/1b1a77855df344e2945d81056d4e10f6
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4
Akademický článek
Quality Recovery for Image Recognition
Autor: Motohiro Takagi, Akito Sakurai, Masafumi Hagiwara
Publikováno v: IEEE Access, Vol 7, Pp 105851-105862 (2019)
This paper proposes a quality recovery network (QRNet) that recovers the image quality from distorted images and improves the classification accuracy for image classification using these recovered images as the classifier inputs, which are optimized
Externí odkaz: https://doaj.org/article/90d4eef371b240c6a0e02e0bb635d3b1
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6
Selective classification considering time series characteristics for spiking neural networks
Autor: Masaya Yumoto, Masafumi Hagiwara
Publikováno v: Neural Network World. 33:49-66
In this paper, we propose new methods for estimating the relative reliability of prediction and rejection methods for selective classification for spiking neural networks (SNNs). We also optimize and improve the efficiency of the RC curve, which repr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6ef60912c89ba2d294a03335069ddc49
https://doi.org/10.14311/nnw.2023.33.004
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8
Akademický článek
Context-sensitive Emotion Estimation for Words. (English)
Autor: Naomu NAGASAWA, Masafumi HAGIWARA
Publikováno v: Transactions of Japan Society of Kansei Engineering; 2024, Vol. 23 Issue 2, p87-96, 10p
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