Results 31 to 40 of about 65,450 (292)

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery [PDF]

, 2020
Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estimation of ...
Baek, Sangsoo, Cha, YoonKyung, Cho, Kyung Hwa, Duan, Hongtao, Kang, Taegu, Kim, Kyunghyun, Kim, Minjeong, Kwon, Yong Sung, Lee, Hyuk, Ligaray, Mayzonee, Pyo, JongCheol   +10 more
core   +1 more source

Earth observations from DSCOVR EPIC instrument [PDF]

, 2018
The National Oceanic and Atmospheric Administration (NOAA) Deep Space Climate Observatory (DSCOVR) spacecraft was launched on 11 February 2015 and in June 2015 achieved its orbit at the first Lagrange point (L1), 1.5 million km from Earth toward the sun.
Blank, Karin, Carn, Simon, Cede, Alexander, Geogdzhayev, Igor, Herman, Jay, Huang, Dong, Huang, Liang-Kang, Knyazikhin, Yuri, Kowalewski, Matthew, Krotkov, Nickolay, Lyapustin, Alexei, Marshak, Alexander, McPeters, Richard, Meyer, Kerry G., Szabo, Adam, Torres, Omar, Yang, Yuekui   +16 more
core   +1 more source

An Attention-Enhanced End-to-End Discriminative Network With Multiscale Feature Learning for Remote Sensing Image Retrieval

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
The discriminative ability of image features plays a decisive role in content-based remote sensing image retrieval (CBRSIR). However, the widely-used convolutional neural networks cannot focus on the discriminative features of important scenes, resulting
Dongyang Hou, Siyuan Wang, Xueqing Tian, Huaqiao Xing   +3 more
doaj   +1 more source

Asymmetric Hash Code Learning for Remote Sensing Image Retrieval [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2022
Remote sensing image retrieval (RSIR), aiming at searching for a set of similar items to a given query image, is a very important task in remote sensing applications. Deep hashing learning as the current mainstream method has achieved satisfactory retrieval performance.
Weiwei Song, Zhi Gao, Renwei Dian, Pedram Ghamisi, Yongjun Zhang, Jon Atli Benediktsson   +5 more
openaire   +2 more sources

Evaluation of Landsat-8 and Sentinel-2A Aerosol Optical Depth Retrievals Across Chinese Cities and Implications for Medium Spatial Resolution Urban Aerosol Monitoring [PDF]

, 2019
In urban environments, aerosol distributions may change rapidly due to building and transport infrastructure and human population density variations.
Huang, Haiyan, Li, Zhongbin, Roy, David P., Vermote, Eric, Zhang, Hankui   +4 more
core   +2 more sources

Attention-Driven Cross-Modal Remote Sensing Image Retrieval

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
In this work, we address a cross-modal retrieval problem in remote sensing (RS) data. A cross-modal retrieval problem is more challenging than the conventional uni-modal data retrieval frameworks as it requires learning of two completely different data representations to map onto a shared feature space.
Chaudhuri, Ushashi, Banerjee, Biplab, Bhattacharya, Avik, Datcu, Mihai   +3 more
openaire   +2 more sources

The Digital Puglia Project: An Active Digital Library of Remote Sensing Data [PDF]

, 1999
The growing need of software infrastructure able to create, maintain and ease the evolution of scientific data, promotes the development of digital libraries in order to provide the user with fast and reliable access to data.
Aloisio, Giovanni, Cafaro, Massimo, Williams, Roy   +2 more
core   +2 more sources

A Content-Based Remote Sensing Image Change Information Retrieval Model

ISPRS International Journal of Geo-Information, 2017
With the rapid development of satellite remote sensing technology, the size of image datasets in many application areas is growing exponentially and the demand for Land-Cover and Land-Use change remote sensing data is growing rapidly. It is thus becoming
Caihong Ma, Wei Xia, Fu Chen, Jianbo Liu, Qin Dai, Liyuan Jiang, Jianbo Duan, Wei Liu   +7 more
doaj   +1 more source

Parameter-Efficient Transfer Learning for Remote Sensing Image–Text Retrieval

IEEE Transactions on Geoscience and Remote Sensing, 2023
Vision-and-language pre-training (VLP) models have experienced a surge in popularity recently. By fine-tuning them on specific datasets, significant performance improvements have been observed in various tasks. However, full fine-tuning of VLP models not only consumes a significant amount of computational resources but also has a significant ...
Yuan Yuan, Yang Zhan, Zhitong Xiong
openaire   +2 more sources

Deep Unsupervised Embedding for Remote Sensing Image Retrieval Using Textual Cues

Applied Sciences, 2020
Compared to image-image retrieval, text-image retrieval has been less investigated in the remote sensing community, possibly because of the complexity of appropriately tying textual data to respective visual representations.
Mohamad M. Al Rahhal, Yakoub Bazi, Taghreed Abdullah, Mohamed L. Mekhalfi, Mansour Zuair   +4 more
doaj   +1 more source