AIMC Topic: Remote Sensing Technology

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TGF-Net: Transformer and gist CNN fusion network for multi-modal remote sensing image classification.

PloS one
In the field of earth sciences and remote exploration, the classification and identification of surface materials on earth have been a significant research area that poses considerable challenges in recent times. Although deep learning technology has...

Change analysis of surface water clarity in the Persian Gulf and the Oman Sea by remote sensing data and an interpretable deep learning model.

Environmental science and pollution research international
The health of an ecosystem and the quality of water can be determined by the clarity of the water. The Persian Gulf and Oman Sea have a unique ecosystem, and monitoring their water clarity is necessary for sustainable development. Here, various crite...

SugarViT-Multi-objective regression of UAV images with Vision Transformers and Deep Label Distribution Learning demonstrated on disease severity prediction in sugar beet.

PloS one
Remote sensing and artificial intelligence are pivotal technologies of precision agriculture nowadays. The efficient retrieval of large-scale field imagery combined with machine learning techniques shows success in various tasks like phenotyping, wee...

Sorghum yield prediction based on remote sensing and machine learning in conflict affected South Sudan.

Scientific reports
Sorghum cultivation plays a pivotal role in addressing food insecurity in South Sudan, but persistent conflict continues to impose challenges in the agriculture sector therefore understanding the impact of conflict on sorghum yield prediction is impo...

Combining deep learning and machine learning techniques to track air pollution in relation to vegetation cover utilizing remotely sensed data.

Journal of environmental management
The rapid urban expansion in Dhaka, the capital of Bangladesh, has escalated air pollution levels and led to a significant decrease in green spaces. This study employed machine learning (ML) and deep learning (DL) techniques to examine the relationsh...

Integration of remote sensing and machine learning algorithm for agricultural drought early warning over Genale Dawa river basin, Ethiopia.

Environmental monitoring and assessment
Drought remains a menace in the Horn of Africa; as a result, the Ethiopia's Genale Dawa River Basin is one of the most vulnerable to agricultural drought. Hence, this study integrates remote sensing and machine learning algorithm for early warning id...

Pan-sharpening via Symmetric Multi-Scale Correction-Enhancement Transformers.

Neural networks : the official journal of the International Neural Network Society
Pan-sharpening is a widely employed technique for enhancing the quality and accuracy of remote sensing images, particularly in high-resolution image downstream tasks. However, existing deep-learning methods often neglect the self-similarity in remote...

Retrieval of nicotine content in cigar leaves by remote analysis of aerial hyperspectral combining machine learning methods.

Scientific reports
Cigar leaf is a special type of tobacco plant, which is the raw material for producing high-quality cigars. The content and proportion of nicotine and other composite substances of cigar leaves have a crucial impact on their quality and vary greatly ...

U3UNet: An accurate and reliable segmentation model for forest fire monitoring based on UAV vision.

Neural networks : the official journal of the International Neural Network Society
Forest fires pose a serious threat to the global ecological environment, and the critical steps in reducing the impact of fires are fire warning and real-time monitoring. Traditional monitoring methods, like ground observation and satellite sensing, ...

SAASNets: Shared attention aggregation Siamese networks for building change detection in multispectral remote sensing.

PloS one
Interfered by external factors, the receptive field limits the traditional CNN multispectral remote sensing building change detection method. It is difficult to obtain detailed building changes entirely, and redundant information is reused in the enc...