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Agarose Gel Characterization for the Fabrication of Brain Tissue Phantoms for Infrared Multispectral Vision Systems

Efraín Albor-Ramírez, Miguel Reyes-Alberto, Luis M. Vidal-Flores, Enoch Gutierrez-Herrera et al. • Gels (2023)

Synthetic phantoms that recreate the characteristics of biological tissues are valuable tools for systematically studying and comprehending physiologies, pathologies, and biological processes related to tissues. The reproduction of mechanic...

DOAJ Open Access (DOAJ) DOI: 10.3390/gels9120944

Validation of Sentinel-2 (MSI) and Sentinel-3 (OLCI) Water Quality Products in Turbid Estuaries Using Fixed Monitoring Stations

Mhd. Suhyb Salama, Lazaros Spaias, Kathrin Poser, Steef Peters et al. • Frontiers in Remote Sensing (2022)

It is common in estuarine waters to place fixed monitoring stations, with the advantages of easy maintenance and continuous measurements. These two features make fixed monitoring stations indispensable for understanding the optical complexi...

DOAJ Open Access (DOAJ) DOI: 10.3389/frsen.2021.808287

Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach

Daniel Jensen, Marc Simard, Kyle Cavanaugh, Yongwei Sheng et al. • Remote Sensing (2019)

The deposition of suspended sediment is an important process that helps wetlands accrete surface material and maintain elevation in the face of sea level rise. Optical remote sensing is often employed to map total suspended solids (TSS), th...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs11131629

Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery

Wassim Bouachir, Koffi Eddy Ihou, Houssem-Eddine Gueziri, Nizar Bouguila et al. • IEEE Access (2019)

Mechanical site preparation by mounding is often used by the forest industry to provide optimal growth conditions for tree seedlings. Prior to planting, an essential step consists in estimating the number of mounds at each planting block, w...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2923765

Automatic building detection and land use classification in urban areas using multispectral high-spatial resolution imagery and LiDAR data

Txomin Hermosilla • ELCVIA Electronic Letters on Computer Vision and Image Analysis (2014)

Urban areas areimportant environments, accounting for approximately half the population of theworld. Cities attract residents partly because they offer ample opportunitiesfor development, which often results in urban sprawl and its complex ...

DOAJ Open Access (DOAJ) DOI: 10.5565/rev/elcvia.584

Systemic Review and Meta-Analysis: The Application of AI-Powered Drone Technology with Computer Vision and Deep Learning Networks in Waste Management

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

Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning—A Comparison between High-End and Low-Cost Multispectral Sensors

Anna Teresa Seiche, Lucas Wittstruck, Thomas Jarmer • Sensors (2024)

In order to meet the increasing demand for crops under challenging climate conditions, efficient and sustainable cultivation strategies are becoming essential in agriculture. Targeted herbicide use reduces environmental pollution and effect...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24051544

Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery

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

Aerosol Optical Depth Retrieval from MODIS Using a Physically Informed Machine Learning Framework

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

SSMSFuse: A Spectral and Spatial Multiscale Coupling Fusion Model for Hyperspectral and Multispectral Image

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