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Academic Articles & Research Papers
Showing 20 of 296 academic articles
Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing
(2018)
Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs10071119
Mikhail Ivanenko, Damian Wanta, Waldemar T. Smolik, Przemysław Wróblewski et al. • Life
(2024)
This study investigated the potential of machine-learning-based stroke image reconstruction in capacitively coupled electrical impedance tomography. The quality of brain images reconstructed using the adversarial neural network (cGAN) was e...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/life14030419
Zhiqiang Gong, Ping Zhong, Weidong Hu • IEEE Access
(2019)
Machine learning methods have achieved good performance and been widely applied in various real-world applications. They can learn the model adaptively and be better fit for special requirements of different tasks. Generally, a good machine...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/access.2019.2917620
J. W. Njoroge, M. Koeva, M. Farnaghi, D. Petrova-Antonova et al. • ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(2026)
Digital twins are increasingly used in smart buildings to monitor energy use. This requires reliable sensor data, geospatial information, and semantically rich 3D building geometry. However, building sensor data often has inconsistent sampl...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/isprs-annals-XII-4-W1-2026-251-2026
Lianlin Li, Hengxin Ruan, Che Liu, Ying Li et al. • Nature Communications
(2019)
Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we e...
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DOI: https://doi.org/10.1038/s41467-019-09103-2
PMC: 6403242
Zigeng Song, Yan Bai, Difeng Wang, Teng Li et al. • Remote Sensing
(2021)
With the implementation of the 2018–2020 Clean Air Action Plan (CAAP) the and impact from COVID-19 lockdowns in 2020, air pollution emissions in central and eastern China have decreased markedly. Here, by combining satellite remote sensing,...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13132525
Charles Nickmilder, Anthony Tedde, Isabelle Dufrasne, Françoise Lessire et al. • Remote Sensing
(2021)
Accurate information about the available standing biomass on pastures is critical for the adequate management of grazing and its promotion to farmers. In this paper, machine learning models are developed to predict available biomass express...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13030408
Mohamad Kazemi, Atefeh Jafarpoor, Youssef Ahmadi, Raoof Mostafazadeh • Scientific Reports
(2026)
Abstract The expansion of human activities and environmental changes in coastal desert and semi-desert ecosystems significantly impact habitat quality. This study used remote sensing data on the Google Earth Engine (GEE) platform to generat...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-47305-z
Juliana Aparecida Anochi, Vinícius Albuquerque de Almeida, Haroldo Fraga de Campos Velho • Remote Sensing
(2021)
Many natural disasters in South America are linked to meteorological phenomena. Therefore, forecasting and monitoring climatic events are fundamental issues for society and various sectors of the economy. In the last decades, machine learni...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13132468
David John Lary, Amir H. Alavi, Amir H. Gandomi, Annette L. Walker • Geoscience Frontiers
(2015)
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.gsf.2015.07.003
Tianchen Liang, Linqing Zou, Qiaoning He, Lin Sun • Remote Sensing
(2026)
Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs18172862
Feiyun Cui, Yun Yue, Yi Zhang, Ziming Zhang et al. • ACS Sensors
(2020)
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, es...
OPENALEX
DOI: https://doi.org/10.1021/acssensors.0c01424
Mafalda Reis Pereira, Mafalda Reis Pereira, Filipe Neves dos Santos, Fernando Tavares et al. • Frontiers in Plant Science
(2023)
Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpls.2023.1242201
G. Baaklini, G. Baaklini, R. El Hourany, M. Fakhri et al. • Ocean Science
(2022)
The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping t...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/os-18-1491-2022
Nicodemo Abate, Diego Ronchi, Sara Elettra Zaia, Gabriele Ciccone et al. • Land
(2025)
This study presents a multi-resolution and multi-temporal remote sensing approach to assess human-induced changes in cultural landscapes, with a focus on the archaeological site of Amrit (Syria) within the MapDam project. By integrating sat...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/land14112233
Majid Riaz, Pedro Guerra, Raffaele Gravina • Sensors
(2025)
This paper introduces an innovative EEG sensor-based computational framework that establishes a pioneering nexus between personality trait quantification and neural dynamics, leveraging biosignal processing of brainwave activity to elucidat...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s25247634
Galen Richardson, Sylvain G. Leblanc, Julie Lovitt, Krishan Rajaratnam et al. • Drones
(2021)
Relating ground photographs to UAV orthomosaics is a key linkage required for accurate multi-scaled lichen mapping. Conventional methods of multi-scaled lichen mapping, such as random forest models and convolutional neural networks, heavily...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/drones5030099
Amanuel Kumsa Bojer, Muluneh Woldetsadik Abshare, Fitsum Mesfin, Ayad M. Fadhil Al-Quraishi • Scientific Reports
(2025)
Abstract Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spati...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-03493-8
Siyuan Liu, Yingchao Fan, Qi Hu, Bing Li et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2025)
Hyperspectral image (HSI) has more spectral information than conventional images, which helps to distinguish targets in a complex scene more accurately. However, HSI typically has a low spatial resolution, which limits their application sce...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2025.3586076
Ł. Wilk, Ł. Wilk, D. Mielczarek, W. Ostrowski et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(2022)
The use of deep machine learning methods for semantic classification of city mesh models is one of the current trends in geoscience development. Thanks to the thriving development of Convolutional Neural Networks (CNNs) it is now achievable...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/isprs-archives-XLIII-B2-2022-485-2022