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Satellite Imagery

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Application of local fully Convolutional Neural Network combined with YOLO v5 algorithm in small target detection of remote sensing image.

PloS one
This exploration primarily aims to jointly apply the local FCN (fully convolution neural network) and YOLO-v5 (You Only Look Once-v5) to the detection of small targets in remote sensing images. Firstly, the application effects of R-CNN (Region-Convol...

A novel semi-supervised framework for UAV based crop/weed classification.

PloS one
Excessive use of agrochemicals for weed controlling infestation has serious agronomic and environmental repercussions associated. An appropriate amount of pesticide/ chemicals is essential for achieving the desired smart farming and precision agricul...

UAV and Machine Learning Based Refinement of a Satellite-Driven Vegetation Index for Precision Agriculture.

Sensors (Basel, Switzerland)
Precision agriculture is considered to be a fundamental approach in pursuing a low-input, high-efficiency, and sustainable kind of agriculture when performing site-specific management practices. To achieve this objective, a reliable and updated descr...

Deep Learning to Unveil Correlations between Urban Landscape and Population Health.

Sensors (Basel, Switzerland)
The global healthcare landscape is continuously changing throughout the world as technology advances, leading to a gradual change in lifestyle. Several diseases such as asthma and cardiovascular conditions are becoming more diffuse, due to a rise in ...

Intelligence in injury prevention: artificial and otherwise.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention

Alcohol outlets and firearm violence: a place-based case-control study using satellite imagery and machine learning.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
INTRODUCTION: This article proposes a novel method for matching places based on visual similarity, using high-resolution satellite imagery and machine learning. This approach strengthens comparisons when the built environment is a potential confounde...

On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network.

PloS one
This research work aims to develop a deep learning-based crop classification framework for remotely sensed time series data. Tobacco is a major revenue generating crop of Khyber Pakhtunkhwa (KP) province of Pakistan, with over 90% of the country's To...

Convcast: An embedded convolutional LSTM based architecture for precipitation nowcasting using satellite data.

PloS one
Nowcasting of precipitation is a difficult spatiotemporal task because of the non-uniform characterization of meteorological structures over time. Recently, convolutional LSTM has been shown to be successful in solving various complex spatiotemporal ...

Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery.

Scientific reports
Recent technological advances in remote sensing sensors and platforms, such as high-resolution satellite imagers or unmanned aerial vehicles (UAV), facilitate the availability of fine-grained earth observation data. Such data reveal vegetation canopi...