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Agriculture

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Predicting rice yield at pixel scale through synthetic use of crop and deep learning models with satellite data in South and North Korea.

The Science of the total environment
Prediction of rice yields at pixel scale rather than county scale can benefit crop management and scientific understanding because it is useful for monitoring how crop yields respond to various agricultural systems and environmental factors. In this ...

Quantitative estimation of soil properties using hybrid features and RNN variants.

Chemosphere
Estimating soil properties is important for maximizing the production of crops in sustainable agriculture. The hyperspectral data next input depends upon the previous one, and the current techniques do not take advantage of this sequential nature of ...

Weakly Supervised Crop Area Segmentation for an Autonomous Combine Harvester.

Sensors (Basel, Switzerland)
Machine vision with deep learning is a promising type of automatic visual perception for detecting and segmenting an object effectively; however, the scarcity of labelled datasets in agricultural fields prevents the application of deep learning to ag...

Farm robots: ecological utopia or dystopia?

Trends in ecology & evolution
Farm robots may lead to an ecological utopia where swarms of small robots help in overcoming the yield penalties and labor requirements associated with agroecological farming - or a dystopia with large robots cultivating monocultures. Societal discus...

Deep Learning Based Prediction on Greenhouse Crop Yield Combined TCN and RNN.

Sensors (Basel, Switzerland)
Currently, greenhouses are widely applied for plant growth, and environmental parameters can also be controlled in the modern greenhouse to guarantee the maximum crop yield. In order to optimally control greenhouses' environmental parameters, one ind...

SmartSpectrometer-Embedded Optical Spectroscopy for Applications in Agriculture and Industry.

Sensors (Basel, Switzerland)
The ongoing digitization of industry and agriculture can benefit significantly from optical spectroscopy. In many cases, optical spectroscopy enables the estimation of properties such as substance concentrations and compositions. Spectral data can be...

3D Reconstruction of Non-Rigid Plants and Sensor Data Fusion for Agriculture Phenotyping.

Sensors (Basel, Switzerland)
Technology has been promoting a great transformation in farming. The introduction of robotics; the use of sensors in the field; and the advances in computer vision; allow new systems to be developed to assist processes, such as phenotyping, of crop's...

The Concept of the Constructional Solution of the Working Section of a Robot for Harvesting Strawberries.

Sensors (Basel, Switzerland)
Strawberry fruits are products of high commercial and consumption value, and, at the same time, they are difficult to harvest due to their very low mechanical strength and difficulties in identifying them within the bush. Therefore, robots collecting...

Graph Regularized Flow Attention Network for Video Animal Counting From Drones.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a large-scale video based animal counting dataset collected by drones (AnimalDrone) for agriculture and wildlife protection. The dataset consists of two subsets, i.e., PartA captured on site by drones and PartB collected fro...

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...