[HTML][HTML] Recent advances of hyperspectral imaging technology and applications in agriculture

B Lu, PD Dao, J Liu, Y He, J Shang - Remote Sensing, 2020 - mdpi.com
Remote sensing is a useful tool for monitoring spatio-temporal variations of crop
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

MH Saleem, J Potgieter, KM Arif - Precision Agriculture, 2021 - Springer
Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …

Deep learning in environmental remote sensing: Achievements and challenges

Q Yuan, H Shen, T Li, Z Li, S Li, Y Jiang, H Xu… - Remote sensing of …, 2020 - Elsevier
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 …

An ARIMA-LSTM model for predicting volatile agricultural price series with random forest technique

S Ray, A Lama, P Mishra, T Biswas, SS Das… - Applied Soft …, 2023 - Elsevier
Abstract Machine learning mechanism is establishing itself as a promising area for
modelling and forecasting complex time series over conventional statistical models. In this …

Deep learning meets SAR: Concepts, models, pitfalls, and perspectives

XX Zhu, S Montazeri, M Ali, Y Hua… - … and Remote Sensing …, 2021 - ieeexplore.ieee.org
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 …

[HTML][HTML] From parcel to continental scale–A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations

R d'Andrimont, A Verhegghen, G Lemoine… - Remote sensing of …, 2021 - Elsevier
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 …

[HTML][HTML] Temporal convolutional neural network for the classification of satellite image time series

C Pelletier, GI Webb, F Petitjean - Remote Sensing, 2019 - mdpi.com
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 …

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 …

Boost precision agriculture with unmanned aerial vehicle remote sensing and edge intelligence: A survey

J Liu, J ** via a multi-source deep learning architecture
D Ienco, R Interdonato, R Gaetano… - ISPRS Journal of …, 2019 - Elsevier
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 …