Results 1 to 10 of about 12,017 (266)

RS-DARTS: A Convolutional Neural Architecture Search for Remote Sensing Image Scene Classification [PDF]

Remote Sensing, 2021
Due to the superiority of convolutional neural networks, many deep learning methods have been used in image classification. The enormous difference between natural images and remote sensing images makes it difficult to directly utilize or modify existing CNN models for remote sensing scene classification tasks.
Zhen Zhang, Shanghao Liu, Yang Zhang, Wenbo Chen   +3 more
openaire   +4 more sources

RS-WaterQuality Mapper: an open-source water quality remote sensing toolbox in QGIS. [PDF]

Earth Sci Inform
Su H, Liu H, Wang L, Miliutina E, Men J, Tian D, Lu Y, Shu S, Beck R, Premsagar A.   +9 more
europepmc   +3 more sources

AGDATABOX-RS computational application: Remote sensing data management

SoftwareX, 2023
Remote sensing can help evolution of agricultural practices by providing periodic information about the status of a given crop over the harvest season, at different scales, and for different segments. Applications in precision agriculture use remote sensing practices based on multispectral images to measure plants’ parameters throughout their ...
Giuvane Conti, Erivelto Mercante, Eduardo Godoy de Souza, Ricardo Sobjak, Claudio Leones Bazzi   +4 more
openaire   +2 more sources

RS-MetaNet: Deep Metametric Learning for Few-Shot Remote Sensing Scene Classification [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2021
13 pages, 11 ...
Haifeng Li 0007, Zhenqi Cui, Zhiqiang Zhu, Li Chen 0025, Jiawei Zhu, Haozhe Huang, Chao Tao 0001   +6 more
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MIX-RS: A Multi-Indexing System Based on HDFS for Remote Sensing Data Storage

Tsinghua Science and Technology, 2022
A large volume of remote sensing (RS) data has been generated with the deployment of satellite technologies. The data facilitates research in ecological monitoring, land management and desertification, etc. The characteristics of RS data (e.g., enormous volume, large single-file size and demanding requirement of fault tolerance) make the Hadoop ...
Jiashu Wu, Jingpan Xiong, Hao Dai, Yang Wang 0006, Chengzhong Xu 0001   +4 more
openaire   +2 more sources

RS-YOLOX: A High-Precision Detector for Object Detection in Satellite Remote Sensing Images

Applied Sciences, 2022
Automatic object detection by satellite remote sensing images is of great significance for resource exploration and natural disaster assessment. To solve existing problems in remote sensing image detection, this article proposes an improved YOLOX model for satellite remote sensing image automatic detection. This model is named RS-YOLOX.
Lei Yang, Guowu Yuan, Hao Zhou, Hongyu Liu, Jian Chen, Hao Wu   +5 more
openaire   +3 more sources

VİSKON-RS: Rapid damage assessment software with remote sensing

2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015
After a disaster, a rapid damage assessment is required for coordinating emergency response teams and planning emergency aid. In this study, in line with AFAD requirements, ViSKON-RS software was developed for the aim of using disaster damage assessment by analysing images obtained via remote(space/air) imaging technologies.
Fatih Kahraman, Mumin Imamoglu, Busra Yuksel Ozcan, Cengiz Huroglu, Tolga Alasag, Omer Faruk Gemici, Muhammet A. Hocaoglu, Hasan F. Ates   +7 more
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RS-DeepSuperLearner: fusion of CNN ensemble for remote sensing scene classification

Annals of GIS, 2023
ABSTRACTScene classification is an important problem in remote sensing (RS) and has attracted a lot of research in the past decade. Nowadays, most proposed methods are based on deep convolutional neural network (CNN) models, and many pretrained CNN models have been investigated.
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SIOS’s Earth Observation (EO), Remote Sensing (RS), and Operational Activities in Response to COVID-19 [PDF]

Remote Sensing, 2021
Svalbard Integrated Arctic Earth Observing System (SIOS) is an international partnership of research institutions studying the environment and climate in and around Svalbard. SIOS is developing an efficient observing system, where researchers share technology, experience, and data, work together to close knowledge gaps, and decrease the environmental ...
Shridhar D. Jawak, Bo N. Andersen, Veijo A. Pohjola, Øystein Godøy, Christiane Hübner, Inger Jennings, Dariusz Ignatiuk, Kim Holmén, Agnar Sivertsen, Richard Hann, Hans Tømmervik, Andreas Kääb, Malgorzata Blaszczyk, Roberto Salzano, Bartlomiej Luks, Kjell Arild Høgda, Rune Storvold, Lennart Nilsen, Rosamaria Salvatori, Kottekkatu Padinchati Krishnan, Sourav Chatterjee, Dag A. Lorentzen, Rasmus Erlandsson, Tom Rune Lauknes, Eirik Malnes, Stein Rune Karlsen, Hiroyuki Enomoto, Ann Mari Fjæraa, Jie Zhang, Sabine Marty, Knut Ove Nygård, Heikki Lihavainen   +31 more
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YOLO-RS: A More Accurate and Faster Object Detection Method for Remote Sensing Images

Remote Sensing, 2023
In recent years, object detection based on deep learning has been widely applied and developed. When using object detection methods to process remote sensing images, the trade-off between the speed and accuracy of models is necessary, because remote sensing images pose additional difficulties such as complex backgrounds, small objects, and dense ...
Tianyi Xie, Wen Han, Sheng Xu 0003
openaire   +2 more sources