A systematic review on hyperspectral imaging technology with a machine and deep learning methodology for agricultural applications

A Khan, AD Vibhute, S Mali, CH Patil - Ecological Informatics, 2022 - Elsevier
The globe's population is increasing day by day, which causes the severe problem of
organic food for everyone. Farmers are becoming progressively conscious of the need to …

[HTML][HTML] Deep learning-based change detection in remote sensing images: A review

A Shafique, G Cao, Z Khan, M Asad, M Aslam - Remote Sensing, 2022 - mdpi.com
Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …

[HTML][HTML] Internet of Things and smart sensors in agriculture: Scopes and challenges

P Rajak, A Ganguly, S Adhikary… - Journal of Agriculture and …, 2023 - Elsevier
Agriculture is an essential sector needed for survival of the human community. Several
measures have been taken to enhance the crop production. However harsh environmental …

Crop type classification by DESIS hyperspectral imagery and machine learning algorithms

N Farmonov, K Amankulova, J Szatmári… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Developments in space-based hyperspectral sensors, advanced remote sensing, and
machine learning can help crop yield measurement, modelling, prediction, and crop …

Land use and land cover classification with hyperspectral data: A comprehensive review of methods, challenges and future directions

MA Moharram, DM Sundaram - Neurocomputing, 2023 - Elsevier
Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …

[HTML][HTML] A systematic review of hyperspectral imaging in precision agriculture: Analysis of its current state and future prospects

BG Ram, P Oduor, C Igathinathane, K Howatt… - … and Electronics in …, 2024 - Elsevier
Hyperspectral sensor adaptability in precision agriculture to digital images is still at its
nascent stage. Hyperspectral imaging (HSI) is data rich in solving agricultural problems like …

Multiple-layer image encryption utilizing fractional-order chen hyperchaotic map and cryptographically secure prngs

W Alexan, N Alexan, M Gabr - Fractal and Fractional, 2023 - mdpi.com
Image encryption is increasingly becoming an important area of research in information
security and network communications as digital images are widely used in various …

[HTML][HTML] Computer vision in smart agriculture and precision farming: Techniques and applications

S Ghazal, A Munir, WS Qureshi - Artificial Intelligence in Agriculture, 2024 - Elsevier
The transformation of age-old farming practices through the integration of digitization and
automation has sparked a revolution in agriculture that is driven by cutting-edge computer …

[HTML][HTML] Advancement of remote sensing for soil measurements and applications: A comprehensive review

MI Abdulraheem, W Zhang, S Li, AJ Moshayedi… - Sustainability, 2023 - mdpi.com
Remote sensing (RS) techniques offer advantages over other methods for measuring soil
properties, including large-scale coverage, a non-destructive nature, temporal monitoring …

A review on the combination of deep learning techniques with proximal hyperspectral images in agriculture

JGA Barbedo - Computers and Electronics in Agriculture, 2023 - Elsevier
Hyperspectral images can capture the spectral characteristics of surfaces and objects,
providing a 2-D spacial component to the spectral profiles found in a given scene. There are …