Zobrazeno 1 - 10 of 30 pro vyhledávání: '"Shuhei Hikosaka"'
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Akademický článek
Image-to-Image Subpixel Registration Based on Template Matching of Road Network Extracted by Deep Learning
Autor: Shuhei Hikosaka, Hideyuki Tonooka
Publikováno v: Remote Sensing, Vol 14, Iss 21, p 5360 (2022)
The vast digital archives collected by optical remote sensing observations over a long period of time can be used to determine changes in the land surface and this information can be very useful in a variety of applications. However, accurate change
Externí odkaz: https://doaj.org/article/a6b1e98ae2ae4dffb523dfc8e0cf4522
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CNN-based generation of high-accuracy urban distribution maps utilising SAR satellite imagery for short-term change monitoring
Autor: Riho Ito, Shota Iino, Tomoyuki Imaizumi, Kento Doi, Shuhei Hikosaka
Publikováno v: International Journal of Image and Data Fusion. 9:302-318
Urban areas in developing countries are experiencing rapid growth, and monitoring short-term changes has become increasingly important. For short-term monitoring, constant observation and generation of high-accuracy urban distribution maps without no
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c93d0336403ad38e47249a5eec133522
https://doi.org/10.1080/19479832.2018.1491897
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4
Classification of Rare Building Change Using CNN with Multi-Class Focal Loss
Autor: Keisuke Nemoto, Shuhei Hikosaka, Ryuhei Hamaguchi, Tomoyuki Imaizumi
Publikováno v: IGARSS
In the remote sensing, supervised deep learning has recently achieved great success of information extraction. However, it requires a large training data in order to effectively learn. In building change classifications, collecting such training data
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5da218cc2148ac9839b2964c9f69b151
https://doi.org/10.1109/igarss.2018.8517563
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5
Detecting Buildings of any Size Using Integration of Cnn Models
Autor: Keisuke Nemoto, Tomoyuki Imaizumi, Ryuhei Hamaguchi, Shuhei Hikosaka
Publikováno v: IGARSS
Buildings in remote sensing imagery have a wide variation in their size. These buildings of different sizes are also very different in their appearance. Although recent CNN based methods show remarkably high performance in building detection task, pr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f89fa777d6e0fbb982574e38f00a200a
https://doi.org/10.1109/igarss.2018.8517887
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6
Building Detection from Satellite Imagery using Ensemble of Size-Specific Detectors
Autor: Ryuhei Hamaguchi, Shuhei Hikosaka
Publikováno v: CVPR Workshops
In recent years, convolutional neural networks (CNNs) show remarkably high performance in building detection tasks. While much progress has been made, there are two aspects that have not been considered well in the past: how to address a wide variati
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dacc5812a1e8b1864234022991be4289
https://doi.org/10.1109/cvprw.2018.00041
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7
Generating high-accuracy urban distribution map for short-term change monitoring based on convolutional neural network by utilizing SAR imagery
Autor: Kento Doi, Shota Iino, Tomoyuki Imaizumi, Riho Ito, Shuhei Hikosaka
Publikováno v: Earth Resources and Environmental Remote Sensing/GIS Applications VIII.
In the developing countries, urban areas are expanding rapidly. With the rapid developments, a short term monitoring of urban changes is important. A constant observation and creation of urban distribution map of high accuracy and without noise pollu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a3068c139cec1d39b66056c6b9fdca51
https://doi.org/10.1117/12.2277901
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Building change detection via a combination of CNNs using only RGB aerial imageries
Autor: Ryuhei Hamaguchi, Keisuke Nemoto, Masakazu Sato, Aito Fujita, Tomoyuki Imaizumi, Shuhei Hikosaka
Publikováno v: Remote Sensing Technologies and Applications in Urban Environments II.
Building change information extracted from remote sensing imageries is important for various applications such as urban management and marketing planning. The goal of this work is to develop a methodology for automatically capturing building changes
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3b44004acdd45abb675363be88582f1f
https://doi.org/10.1117/12.2277912
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9
Damage detection from aerial images via convolutional neural networks
Autor: Ryosuke Nakamura, Aito Fujita, Ken Sakurada, Shuhei Hikosaka, Riho Ito, Tomoyuki Imaizumi
Publikováno v: MVA
This paper explores the effective use of Convolutional Neural Networks (CNNs) in the context of washed-away building detection from pre- and post-tsunami aerial images. To this end, we compile a dedicated, labeled aerial image dataset to construct mo
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8fa5ff3f0a6348df1e96fb82426c551b
https://doi.org/10.23919/mva.2017.7986759
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10
Effective Use of Dilated Convolutions for Segmenting Small Object Instances in Remote Sensing Imagery
Autor: Ryuhei Hamaguchi, Tomoyuki Imaizumi, Aito Fujita, Shuhei Hikosaka, Keisuke Nemoto
Publikováno v: WACV
Thanks to recent advances in CNNs, solid improvements have been made in semantic segmentation of high resolution remote sensing imagery. However, most of the previous works have not fully taken into account the specific difficulties that exist in rem
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4176fbb27c02c614b4d5cef26d201f49
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