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Academic Articles & Research Papers
Showing 20 of 296 academic articles
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...
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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 ...
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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...
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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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DOI: https://doi.org/10.1016/j.jag.2021.102456
Shiqi Feng, Xuquan Wang, Xiong Dun, Zhanshan Wang et al. • IEEE Photonics Journal
(2025)
Encoded computational hyperspectral cameras, propelled by advances in compressed sensing theory, making both miniaturization and real-time hyperspectral imaging feasible. Spectral-encoded or spatial-encoded hyperspectral imaging strategy ha...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JPHOT.2025.3624799
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...
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Open Access (DOAJ)
DOI: 10.1016/j.srs.2024.100185
Chao-Kai Wen, Wan-Ting Shih, Shi Jin • IEEE Wireless Communications Letters
(2018)
In frequency division duplex mode, the downlink channel state information (CSI) should be sent to the base station through feedback links so that the potential gains of a massive multiple-input multiple-output can be exhibited. However, suc...
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Open Access
DOI: https://doi.org/10.1109/lwc.2018.2818160
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
Tyrone Bright, Sarp Adali, Cristina Trois • Drones
(2025)
As the generation of Municipal Solid Waste (MSW) has exponentially increased, this poses a challenge for waste managers, such as municipalities, to effectively control waste streams. If waste streams are not managed correctly, they negative...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/drones9080550
Swaraja K., Akshitha V., Pranav K., Vyshnavi B. et al. • E3S Web of Conferences
(2021)
Depth estimation is a computer vision technique that is critical for autonomous schemes for sensing their surroundings and predict their own condition. Traditional estimating approaches, such as structure from motion besides stereo vision s...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/e3sconf/202130901069
Yohei Nishizaki, Matias Valdivia, Ryoichi Horisaki, Katsuhisa Kitaguchi et al. • Optics Express
(2019)
We present a new class of wavefront sensors by extending their design space based on machine learning. This approach simplifies both the optical hardware and image processing in wavefront sensing. We experimentally demonstrated a variety of...
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Open Access
DOI: https://doi.org/10.1364/oe.27.000240