Zobrazeno 1 - 10
of 476
pro vyhledávání: '"Jon Atli Benediktsson"'
Autor:
Chen Yang, Xinmei Zhang, Lorenzo Bruzzone, Bin Liu, Dawei Liu, Xin Ren, Jon Atli Benediktsson, Yanchun Liang, Bo Yang, Minghao Yin, Haishi Zhao, Renchu Guan, Chunlai Li, Ziyuan Ouyang
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-9 (2023)
Abstract Lunar surface chemistry is essential for revealing petrological characteristics to understand the evolution of the Moon. Existing chemistry mapping from Apollo and Luna returned samples could only calibrate chemical features before 3.0 Gyr,
Externí odkaz:
https://doaj.org/article/9141e788982d4c1ea0c6fa8eb0ce1a46
Autor:
Bin Zhao, Haukur Isfeld Ragnarsson, Magnus O. Ulfarsson, Gabriele Cavallaro, Jon Atli Benediktsson
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 4180-4193 (2022)
The classification of hyperspectral images (HSIs) is an essential application of remote sensing and it is addressed by numerous publications every year. A large body of these papers present new classification algorithms and benchmark them against est
Externí odkaz:
https://doaj.org/article/cb56629bf55440079a6af90b9baa56ff
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 866-867 (2023)
The eleven papers in this special section serve as a tribute to Professor David A. Landgrebe who is known for his work in the fundamentals of multispectral image processing and analysis. The papers are grouped into three categories: historical and fu
Externí odkaz:
https://doaj.org/article/4092d54e985c4c23977dde30ad372081
Autor:
Lv ZhiYong, FengJun Wang, LinFu Xie, WeiWei Sun, Nicola Falco, Jon Atli Benediktsson, ZhenZhen You
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 10199-10212 (2021)
Change vector analysis (CVA) is a simple yet attractive method to detect changes with remote sensing images. Since its first introduction in 1980, CVA has received increased attention from the remote sensing community, leading to the definition of se
Externí odkaz:
https://doaj.org/article/898187b4dcfc4b34a192f865dae7c150
Autor:
Chen Yang, Haishi Zhao, Lorenzo Bruzzone, Jon Atli Benediktsson, Yanchun Liang, Bin Liu, Xingguo Zeng, Renchu Guan, Chunlai Li, Ziyuan Ouyang
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
Using Chang’E data, the authors here identify more than 109,000 previously unrecognized lunar craters and date almost 19,000 craters based on transfer learning with deep neural networks. A new lunar crater database is derived and distributed to the
Externí odkaz:
https://doaj.org/article/65bb490c6daa4866aab6382029e35f68
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 4575-4584 (2020)
This article presents a novel dual-path full convolutional network (DP-FCN) model for constructing a landslide inventory map (LIM) with bitemporal very high-resolution (VHR) remote sensing images. Unlike traditional methods for drawing LIM, the propo
Externí odkaz:
https://doaj.org/article/6330dc69b0f24c71a4ebbd44f4aed3aa
Publikováno v:
IEEE Access, Vol 7, Pp 34425-34437 (2019)
Land cover change detection (LCCD) based on bitemporal remote sensing images has become a popular topic in the field of remote sensing. Despite numerous methods promoted in recent decades, an improvement on the usability and performance of these meth
Externí odkaz:
https://doaj.org/article/b9e7417fbe894745ae38bb747cf1007f
Autor:
Mohammed Asaad Ghazal, Ali Mahmoud, Ali Aslantas, Ahmed Soliman, Ahmed Shalaby, Jon Atli Benediktsson, Ayman El-Baz
Publikováno v:
IEEE Access, Vol 7, Pp 132563-132576 (2019)
Vegetation is an important parameter in all bio- and ecosystems, and it should be monitored to conserve and restore the environment. This paper presents a design and implementation of a compact system for vegetation cover monitoring, which consists o
Externí odkaz:
https://doaj.org/article/fe9b3dbe7fc940288717a921d3a80b02
Publikováno v:
IEEE Access, Vol 6, Pp 1380-1390 (2018)
Hyperspectral image (HSI) is usually corrupted by various types of noise, including Gaussian noise, impulse noise, stripes, deadlines, and so on. Recently, sparse and low-rank matrix decomposition (SLRMD) has demonstrated to be an effective tool in H
Externí odkaz:
https://doaj.org/article/7188496a5cef4938b57bead5c5376364
Autor:
Fadi Kizel, Jon Atli Benediktsson, Lorenzo Bruzzone, Gro B. M. Pedersen, Olga K. Vilmundardottir, Nicola Falco
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 11, Iss 6, Pp 2047-2058 (2018)
The empirical line (EL) calibration method is commonly used for atmospheric correction of remotely sensed spectral images and recovery of surface reflectance. The current EL-based methods are applicable to calibrate only single images. Therefore, the
Externí odkaz:
https://doaj.org/article/e640904a276f4afcb0e3e004502dc8aa