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[HTML][HTML] Recent advances of hyperspectral imaging technology and applications in agriculture
Remote sensing is a useful tool for monitoring spatio-temporal variations of crop
morphological and physiological status and supporting practices in precision farming. In …
morphological and physiological status and supporting practices in precision farming. In …
Automation in agriculture by machine and deep learning techniques: A review of recent developments
Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …
intelligence techniques and robotic systems. Particularly, with the advancements in machine …
Deep learning in environmental remote sensing: Achievements and challenges
Various forms of machine learning (ML) methods have historically played a valuable role in
environmental remote sensing research. With an increasing amount of “big data” from earth …
environmental remote sensing research. With an increasing amount of “big data” from earth …
An ARIMA-LSTM model for predicting volatile agricultural price series with random forest technique
Abstract Machine learning mechanism is establishing itself as a promising area for
modelling and forecasting complex time series over conventional statistical models. In this …
modelling and forecasting complex time series over conventional statistical models. In this …
Deep learning meets SAR: Concepts, models, pitfalls, and perspectives
Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
[HTML][HTML] From parcel to continental scale–A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations
Detailed parcel-level crop type map** for the whole European Union (EU) is necessary for
the evaluation of agricultural policies. The Copernicus program, and Sentinel-1 (S1) in …
the evaluation of agricultural policies. The Copernicus program, and Sentinel-1 (S1) in …
[HTML][HTML] Temporal convolutional neural network for the classification of satellite image time series
Latest remote sensing sensors are capable of acquiring high spatial and spectral Satellite
Image Time Series (SITS) of the world. These image series are a key component of …
Image Time Series (SITS) of the world. These image series are a key component of …
Sentinel SAR-optical fusion for crop type map** using deep learning and Google Earth Engine
J Adrian, V Sagan, M Maimaitijiang - ISPRS Journal of Photogrammetry and …, 2021 - Elsevier
Accurate crop type map** provides numerous benefits for a deeper understanding of food
systems and yield prediction. Ever-increasing big data, easy access to high-resolution …
systems and yield prediction. Ever-increasing big data, easy access to high-resolution …
Boost precision agriculture with unmanned aerial vehicle remote sensing and edge intelligence: A survey
J Liu, J ** via a multi-source deep learning architecture
The huge amount of data currently produced by modern Earth Observation (EO) missions
has allowed for the design of advanced machine learning techniques able to support …
has allowed for the design of advanced machine learning techniques able to support …