Geolocation Correction for Geostationary Satellite Observations by a Phase-Only Correlation Method Using a Visible Channel

Autor: Hideaki Takenaka, Taiyou Sakashita, Atsushi Higuchi, Teruyuki Nakajima

Publikováno v: Remote Sensing, Vol 12, Iss 15, p 2472 (2020)

This study describes a high-speed correction method for geolocation information of geostationary satellite data for accurate physical analysis. Geostationary satellite observations with high temporal resolution provide instantaneous analysis and prom

Externí odkaz: https://doaj.org/article/1408d1a025a647d8bf015aa7842cd484

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One-shot Learning Landmarks Detection

Autor: Clair Vandersteen, François Patou, Zihao Wang, Hervé Delingette, Nicolas Guevara, Charles Raffaelli

Publikováno v: Lecture Notes in Computer Science
The MICCAI workshop on Data Augmentation, Labeling, and Imperfections
The MICCAI workshop on Data Augmentation, Labeling, and Imperfections, Oct 2021, strasbourg, France. pp.163-172
Deep Generative Models, and Data Augmentation, Labelling, and Imperfections ISBN: 9783030882099
DGM4MICCAI/DALI@MICCAI
MICCAI 2021-Workshop on Data Augmentation, Labeling, and Imperfections
MICCAI 2021-Workshop on Data Augmentation, Labeling, and Imperfections, Oct 2021, strasbourg, France. pp.163-172, ⟨10.1007/978-3-030-88210-5_15⟩

International audience; Landmark detection in medical images is important for many clinical applications. Learning-based landmark detection is successful at solving some problems but it usually requires a large number of annotated datasets for the tr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::671c3080c3df40ead51c0d5a80b70165
https://hal.inria.fr/hal-03024759

Robust ConvNet Landmark-Based Visual Place Recognition by Optimizing Landmark Matching

Autor: Chen Zhangping, Kong Yaguang, Liu Wei

Publikováno v: IEEE Access, Vol 7, Pp 30754-30767 (2019)

Visual place recognition (VPR) is a fundamental but challenging problem that has not been solved completely for a long time, especially in a kaleidoscopic environment. Recent advanced works which exploit ConvNet landmarks as a representation of an im

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7257338464f619eea5fd20e45f5fed14
https://ieeexplore.ieee.org/document/8653820/

Landmark Matching Method about Pointing to the Ground of Three-axis Stabilization Geostationary Remote Sensing Satellite

Autor: DING Lu, TONG Xiaochong, QIN Zhiyuan, LAI Guangling

Publikováno v: Acta Geodaetica et Cartographica Sinica, Vol 47, Iss 11, Pp 1506-1517 (2018)

Geostationary remote sensing satellite is relatively static to the earth.However,because of the influences suffered from inner factors and outer environment,an error of geometric would be happened to satellite's pointing to the ground,and it will cau

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doajarticles::7f7562e2aaf35496536074defc557ea8
http://html.rhhz.net/CHXB/html/2018-11-1506.htm