AIMC Topic: Remote Sensing Technology

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Deep learning approaches in remote sensing of soil organic carbon: a review of utility, challenges, and prospects.

Environmental monitoring and assessment Nov 15, 2021
The use of neural network (NN) models for remote sensing (RS) retrieval of landscape biophysical and biochemical properties has become popular in the last decade. Recently, the emergence of "big data" that can be generated from remotely sensed data a...
Soil Deep Learning Environmental Monitoring Carbon Remote Sensing Technology
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Lightweight Deep Neural Network Method for Water Body Extraction from High-Resolution Remote Sensing Images with Multisensors.

Sensors (Basel, Switzerland) Nov 7, 2021
Rapid and accurate extraction of water bodies from high-spatial-resolution remote sensing images is of great value for water resource management, water quality monitoring and natural disaster emergency response. For traditional water body extraction ...
Neural Networks, Computer Machine Learning Support Vector Machine Remote Sensing Technology Geography
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Learning a Transform Base for the Multi- to Hyperspectral Sensor Network with K-SVD.

Sensors (Basel, Switzerland) Nov 2, 2021
A promising low-cost solution for monitoring spectral information, e.g., on agricultural fields, is that of wireless sensor networks. In contrast to remote sensing, these can achieve more continuous monitoring due to their long-term deployment and ar...
Machine Learning Remote Sensing Technology
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Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data.

Nature plants Oct 4, 2021
Four species of grass generate half of all human-consumed calories. However, abundant biological data on species that produce our food remain largely inaccessible, imposing direct barriers to understanding crop yield and fitness traits. Here, we asse...
Machine Learning Australia Remote Sensing Technology Models, Biological Crops, Agricultural Spacecraft Life History Traits
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Deep learning-based remote sensing estimation of water transparency in shallow lakes by combining Landsat 8 and Sentinel 2 images.

Environmental science and pollution research international Aug 18, 2021
Water transparency is a key indicator of water quality as it reflects the turbidity and eutrophication in lakes and reservoirs. To carry out remote sensing monitoring of water transparency rapidly and intelligently, deep learning technology was used ...
Lakes Deep Learning Environmental Monitoring Remote Sensing Technology Water Quality
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Fast and Accurate Object Detection in Remote Sensing Images Based on Lightweight Deep Neural Network.

Sensors (Basel, Switzerland) Aug 13, 2021
Deep learning-based object detection in remote sensing images is an important yet challenging task due to a series of difficulties, such as complex geometry scene, dense target quantity, and large variant in object distributions and scales. Moreover,...
Neural Networks, Computer Algorithms Remote Sensing Technology
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Deep neural networks based automated extraction of dugong feeding trails from UAV images in the intertidal seagrass beds.

PloS one Aug 13, 2021
Dugongs (Dugong dugon) are seagrass specialists distributed in shallow coastal waters in tropical and subtropical seas. The area and distribution of the dugongs' feeding trails, which are unvegetated winding tracks left after feeding, have been used ...
Neural Networks, Computer Animals Ecosystem Image Processing, Computer-Assisted Remote Sensing Technology Conservation of Natural Resources Feeding Behavior Dugong
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Forecasting of Typhoon-Induced Wind-Wave by Using Convolutional Deep Learning on Fused Data of Remote Sensing and Ground Measurements.

Sensors (Basel, Switzerland) Aug 2, 2021
Taiwan is an island, and its economic activities are primarily dependent on maritime transport and international trade. However, Taiwan is also located in the region of typhoon development in the Northwestern Pacific Basin. Thus, it frequently receiv...
Deep Learning Remote Sensing Technology Internationality Commerce Cyclonic Storms
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Remote Sensing Image Dataset Expansion Based on Generative Adversarial Networks with Modified Shuffle Attention.

Sensors (Basel, Switzerland) Jul 16, 2021
With the development of science and technology, neural networks, as an effective tool in image processing, play an important role in gradual remote-sensing image-processing. However, the training of neural networks requires a large sample database. T...
Neural Networks, Computer Databases, Factual Image Processing, Computer-Assisted Remote Sensing Technology
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Functionalization of remote sensing and on-site data for simulating surface water dissolved oxygen: Development of hybrid tree-based artificial intelligence models.

Marine pollution bulletin Jul 14, 2021
Dissolved oxygen (DO) is an important indicator of river health for environmental engineers and ecological scientists to understand the state of river health. This study aims to evaluate the reliability of four feature selector algorithms i.e., Borut...
Artificial Intelligence Reproducibility of Results Water Remote Sensing Technology Oxygen
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