AIMC Topic: Remote Sensing Technology
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Plastics detection and sorting using hyperspectral sensing and machine learning algorithms.
Waste management (New York, N.Y.)
Jul 15, 2025
Plastic waste second life management requires effective detection (and sorting if necessary) techniques to tackle the environmental challenge it poses. This research explores the application of hyperspectral imaging in the spectral range 900-1700 nm ...
Attribute-guided feature fusion network with knowledge-inspired attention mechanism for multi-source remote sensing classification.
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Land use and land cover (LULC) classification is a popular research area in remote sensing. The information of single-modal data is insufficient for accurate classification, especially in complex scenes, while the complementarity of multi-modal data ...
Advancing Remote Monitoring for Patients With Alzheimer Disease and Related Dementias: Systematic Review.
JMIR aging
May 14, 2025
BACKGROUND: Using remote monitoring technology in the context of Alzheimer disease (AD) care presents exciting new opportunities to lessen caregiver stress and improve patient care quality. The application of wearables, environmental sensors, and sma...
UAV-based water pollutants detection and classification framework using multi-modal and multi-sensor ensemble learning.
Environmental monitoring and assessment
May 9, 2025
The massive increment in water pollutants due to the release of plastic, industrial, and household waste has threatened the delicate balance of ecosystems and the well-being of human life. Therefore, detection and monitoring of such water pollutants ...
Satellite Remote Sensing-Implemented Nontargeted Screening of Emerging Contaminant Fingerprints in a River-to-Ocean Continuum through Interpretable Machine Learning: The Pivotal Intermediary Role of Dissolved Organic Matter.
Environmental science & technology
May 6, 2025
Emerging contaminants (ECs) can exert irreversible health impacts on humans, even at trace concentrations. Currently, nontargeted screening of ECs has been developed for their assessment, which requires sophisticated instrumentation. Although satelli...
Enhancing genomic-based forward prediction accuracy in wheat by integrating UAV-derived hyperspectral and environmental data with machine learning under heat-stressed environments.
The plant genome
Mar 1, 2025
Integrating genomic, hyperspectral imaging (HSI), and environmental data enhances wheat yield predictions, with HSI providing detailed spectral insights for predicting complex grain yield (GY) traits. Incorporating HSI data with single nucleotide pol...
Spatiotemporal Variation Assessment and Improved Prediction Of Cyanobacteria Blooms in Lakes Using Improved Machine Learning Model Based on Multivariate Data.
Environmental management
Mar 1, 2025
Cyanobacterial blooms in shallow lakes pose a significant threat to aquatic ecosystems and public health worldwide, highlighting the urgent need for advanced predictive methodologies. As impounded lakes along the Eastern Route of the South-to-North W...
Computer vision-inspired contrastive learning for self-supervised anomaly detection in sensor-based remote healthcare monitoring.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Sensor-based remote healthcare monitoring is a promising approach for timely detection of adverse health events such as falls or infections in people living with dementia (PLwD) in the home, and reducing preventable hospital admissions. Current anoma...
[Multi-factor Impact Analysis of Grassland Phenology Changes on the Qinghai-Xizang Plateau Based on Interpretable Machine Learning].
Huan jing ke xue= Huanjing kexue
Jun 8, 2024
The vegetation phenology of the Qinghai-Xizang Plateau is changing significantly in the context of climate change. However, there are many hydrothermal factors affecting the phenology, and few studies have focused on the effects of multiple factors o...
Long-term monitoring chlorophyll-a concentration using HJ-1 A/B imagery and machine learning algorithms in typical lakes, a cold semi-arid region.
Optics express
Apr 22, 2024
Chlorophyll a (Chl-a) in lakes serves as an effective marker for assessing algal biomass and the nutritional level of lakes, and its observation is feasible through remote sensing methods. HJ-1 (Huanjing-1) satellite, deployed in 2008, incorporates a...
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