Výsledky vyhledávání - "John Ray Bergado"

Akademický článek

Detection of Informal Settlements from VHR Images Using Convolutional Neural Networks

Autor: Nicholus Mboga, Claudio Persello, John Ray Bergado, Alfred Stein

Publikováno v: Remote Sensing, Vol 9, Iss 11, p 1106 (2017)

Information about the location and extent of informal settlements is necessary to guide decision making and resource allocation for their upgrading. Very high resolution (VHR) satellite images can provide this useful information, however, different u

Externí odkaz: https://doaj.org/article/c2dbf4e9572c489a82d0b95f4e70fd34

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End-to-end predictive models for remote sensing applications

Autor: John Ray Bergado

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdb3331ac8209b0042cf968c18e1ef59
https://doi.org/10.3990/1.9789036550963

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Predicting wildfire burns from big geodata using deep learning

Autor: Claudio Persello, John Ray Bergado, Alfred Stein, Karin Reinke

Publikováno v: Safety science, 140:105276. Elsevier

Wildfire continues to be a major environmental problem in the world. To help land and fire management agencies manage and mitigate wildfire-related risks, we need to develop tools for mapping those risks. Big geodata—in the form of remotely sensed

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a3dc9974e8155316870a96112ba58dc
https://doi.org/10.1016/j.ssci.2021.105276

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Delineation of agricultural fields in smallholder farms from satellite images using fully convolutional networks and combinatorial grouping

Autor: Valentyn A. Tolpekin, R.A. de By, John Ray Bergado, Claudio Persello

Publikováno v: Remote Sensing of Environment
Remote sensing of environment, 231:111253, 1-18. Elsevier

Accurate spatial information of agricultural fields in smallholder farms is important for providing actionable information to farmers, managers, and policymakers. Very High Resolution (VHR) satellite images can capture such information. However, the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5335f3561815e28fdd83abb0ff8579c
https://pubmed.ncbi.nlm.nih.gov/31534278

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Towards automated delineation of smallholder farm fields from VHR images using convolutional networks

Autor: John Ray Bergado, Claudio Persello, Rolf A. de By, Valentyn A. Tolpekin

Publikováno v: 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019-Proceedings, 3836-3839
STARTPAGE=3836;ENDPAGE=3839;TITLE=2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019-Proceedings
IGARSS

Automated delineation of smallholder farm fields is difficult because of their small size, irregular shape and the use of mixed-cropping systems. Edges between smallholder plots are often indistinct in satellite imagery and contours have to be identi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ec51dcee2f2deeefaa9a854fa6b85f5
https://research.utwente.nl/en/publications/a463e6bb-4aea-4c84-ae9d-66f33be3de9a

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Recurrent Multiresolution Convolutional Networks for VHR Image Classification

Autor: Claudio Persello, John Ray Bergado, Alfred Stein

Publikováno v: IEEE transactions on geoscience and remote sensing, 56(11):8388225, 6361-6374. IEEE

Classification of very high-resolution (VHR) satellite images has three major challenges: 1) inherent low intraclass and high interclass spectral similarities; 2) mismatching resolution of available bands; and 3) the need to regularize noisy classifi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e679814b1214e6fe9dcf1dbd92d8d2ad
https://research.utwente.nl/en/publications/6bfddb18-7be0-47cc-af58-4a75713fb3c4

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Classification of multitemporal SAR images using convolutional neural networks and Markov random fields

Autor: Claudio Persello, John Ray Bergado, Valentyn A. Tolpekin, Carolyne Danilla

Publikováno v: IGARSS
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS): 23-28 Jly 2017, Fort Worth Texas, USA, 2231-2234
STARTPAGE=2231;ENDPAGE=2234;TITLE=2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

Classification of Synthetic Aperture Radar (SAR) images is a complex task because of the presence of speckle, which affects images in a way similar to a strong noise. In this study, we investigate the use of Convolutional Neural Networks (CNNs) which

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0709468b34f3c9ffefa458c33d48bca8
https://doi.org/10.1109/igarss.2017.8127432

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Detection of informal settlements from VHR satellite images using convolutional neural networks

Autor: Alfred Stein, Claudio Persello, John Ray Bergado, Nicholus Mboga

Publikováno v: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS): 23-28 July 2017, Fort Worth Texas, USA, 5169-5172
STARTPAGE=5169;ENDPAGE=5172;TITLE=2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
IGARSS

Convolutional neural networks (CNNs), widely studied in the domain of computer vision, are more recently finding application in the analysis of high-resolution aerial and satellite imagery. In this paper, we investigate a deep feature learning approa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90be919b05bb3a00ee6fb84340f1aa37
https://research.utwente.nl/en/publications/9321e763-a1f8-4d1e-a688-800b91542014

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Detection of Informal Settlements from VHR Images Using Convolutional Neural Networks

Autor: John Ray Bergado, Alfred Stein, Nicholus Mboga, Claudio Persello

Publikováno v: Remote sensing, 9(11):1106. MDPI
Remote Sensing, 9 (11
Remote Sensing, Vol 9, Iss 11, p 1106 (2017)
Remote Sensing; Volume 9; Issue 11; Pages: 1106

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50a58247bb5dc603377a9b110135d7e8
https://doi.org/10.3390/rs9111106

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A deep learning approach to the classification of sub-decimetre resolution aerial images

Autor: John Ray Bergado, C.M. Gevaert, Claudio Persello

Publikováno v: Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS) : Advancing the understanding of our living planet, 10-15 July 2016, Beijing, China, 1516-1519
STARTPAGE=1516;ENDPAGE=1519;TITLE=Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS) : Advancing the understanding of our living planet, 10-15 July 2016, Beijing, China
IGARSS

Spatial-contextual features play a vital role in the classification of very high resolution aerial images characterized by sub-decimetre resolution. However, manually extracting relevant contextual features is difficult and time-consuming in the anal

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e588c9b29e8c86adffb2296b0610df8
https://research.utwente.nl/en/publications/e17e9860-6623-482a-b8c5-b6bbf25a42b7

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