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Academic Articles & Research Papers
Showing 20 of 154 academic articles
Klemen Istenič, Nuno Gracias, Aurélien Arnaubec, Javier Escartín et al. • Remote Sensing
(2019)
Rapid developments in the field of underwater photogrammetry have given scientists the ability to produce accurate 3-dimensional (3D) models which are now increasingly used in the representation and study of local areas of interest. This pa...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs11182093
E. Nocerino, F. Lago, D. Morabito, F. Remondino et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(2017)
During the last two decades we have witnessed great improvements in ICT hardware and software technologies. Three-dimensional
content is starting to become commonplace now in many applications. Although for many years 3D technologies have b...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/isprs-archives-XLII-2-W3-535-2017
Kefeng Lv, Yongsheng Zhang, Ying Yu, Zhenchao Zhang et al. • Remote Sensing
(2022)
Visual localization is a core part of many computer vision and geospatial perception applications; however, the ever-changing time phase and environment present challenges. Moreover, the ever-enriching spatial data types and sensors create ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14163983
Jie Lu, Wenpeng Zhang, Yongxiang Liu, Wei Yang • Remote Sensing
(2022)
The fine state of targets can be represented by the extracted micro-Doppler (m-D) components from the radar echo. However, current methods do not consider the specialty of the m-D components, and their performance with non-sinusoidal compon...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14194764
Aleksey Viktorovich Skorokhodov, Sergey Vladimirovich Aksenov, Andrey Vladimirovich Aksenov, Dmitriy Nikolaevich Laykom • Известия Томского политехнического университета: Инжиниринг георесурсов
(2017)
The relevance of the research is caused by the necessity to develop algorithms and software to classify the cloud types based on single-layer cloud on the satellite images received from MODIS spectral radiometer used in Terra and Aqua remot...
DOAJ
Open Access (DOAJ)
Timothée Corchia, Bertrand Bonan, Nemesio Rodríguez-Fernández, Gabriel Colas et al. • Remote Sensing
(2023)
In this work, Advanced SCATterometer (ASCAT) backscatter data are directly assimilated into the interactions between soil, biosphere, and atmosphere (ISBA) land surface model using Meteo-France’s global Land Data Assimilation System (LDAS-M...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs15174258
Jian Liu, Pei Niu, Yihui Jiang, Zilong Zhao et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2026)
Object detection in uncrewed aerial vehicle (UAV) acquired images remains a challenging task due to extreme scale variation, dense object layouts, and complex backgrounds, etc. Although convolutional neural networks (CNNs), transformers, an...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2026.3729713
Peter M. Atkinson, Adrian R. L. Tatnall • International Journal of Remote Sensing
(1997)
Abstract. Over the past decade there have been considerable increases in both the quantity of remotely sensed data available and the use of neural networks. These increases have largely taken place in parallel, and it is only recently that ...
OPENALEX
DOI: https://doi.org/10.1080/014311697218700
Yuchao Feng, Jianwei Zheng, Mengjie Qin, Cong Bai et al. • Remote Sensing
(2021)
Owing to the outstanding feature extraction capability, convolutional neural networks (CNNs) have been widely applied in hyperspectral image (HSI) classification problems and have achieved an impressive performance. However, it is well know...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13214407
Zhenkang Wang, Nan Xia, Jiale Liang, Jiechen Wang • Geo-spatial Information Science
(2026)
China’s rapid urbanization has led to the emergence of urban villages (UVs), whose governance is crucial for urban quality and built environment management. However, conventional identification methods rely on high-resolution remote sensing...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/10095020.2026.2711549
Taikang Yuan, Junxing Zhu, Wuxin Wang, Jingze Lu et al. • Remote Sensing
(2023)
Sea surface temperature (SST) prediction has attracted increasing attention, due to its crucial role in understanding the Earth’s climate and ocean system. Existing SST prediction methods are typically based on either physics-based numerica...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs15143498
Siwei Yu, Jianwei Ma • Reviews of Geophysics
(2021)
Abstract Recently deep learning (DL), as a new data‐driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the...
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DOI: https://doi.org/10.1029/2021rg000742
Lucas Prado Osco, José Marcato, Ana Paula Marques Ramos, Lúcio André de Castro Jorge et al. • International Journal of Applied Earth Observation and Geoinformation
(2021)
Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, ...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.jag.2021.102456
Liurong Tao, Haoran Ren, Zhiwei Gu • Remote Sensing
(2023)
Seismic impedance inversion is a vital way of geological interpretation and reservoir investigation from a geophysical perspective. However, it is inevitably an ill-posed problem due to the noise or the band-limited characteristic of seismi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs15040891
Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia et al. • IEEE Geoscience and Remote Sensing Magazine
(2017)
Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are becoming increasingly important. In particular, deep learning has proven to be both a major breakthrough and an extremely powerful tool in ...
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Open Access
DOI: https://doi.org/10.1109/mgrs.2017.2762307
JongCheol Pyo, Hongtao Duan, Mayzonee Ligaray, Minjeong Kim et al. • Remote Sensing
(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 estim...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs12071073
Senzhang Wang, Jiannong Cao, Philip S. Yu • IEEE Transactions on Knowledge and Data Engineering
(2020)
With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temp...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.3025580
Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing
(2020)
A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...
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DOI: https://doi.org/10.3390/rs12111729
Christopher Ardohain, Songlin Fei • Science of Remote Sensing
(2025)
Deep learning (DL) is ubiquitous in remote sensing analysis with continued evolution in model architectures and advancement of model types. However, DL is still constrained by the need for extensive training datasets, which are costly and t...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.srs.2024.100185
Xiaofei Yang, Yunming Ye, Xutao Li, Raymond Y.K. Lau et al. • IEEE Transactions on Geoscience and Remote Sensing
(2018)
Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem. In contrast to conventional computer vision task...
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DOI: https://doi.org/10.1109/tgrs.2018.2815613