The role of artificial neural network and machine learning in utilizing spatial information
In this age of the fourth industrial revolution 4.0, the digital world has a plethora of data,
including the internet of things, mobile, cybersecurity, social media, forecasts, health data …
including the internet of things, mobile, cybersecurity, social media, forecasts, health data …
Deep learning-based classification methods for remote sensing images in urban built-up areas
Urban areas have been focused recently on the remote sensing applications since their
function closely relates to the distribution of built-up areas, where reflectivity or scattering …
function closely relates to the distribution of built-up areas, where reflectivity or scattering …
Satellite image classification with data augmentation and convolutional neural network
Satellite image classification is helpful in many real-time applications for better utilization of
area and to get deep information from it. It is difficult to classify them as they are having high …
area and to get deep information from it. It is difficult to classify them as they are having high …
Semantic segmentation and detection of satellite objects using U-Net model of deep learning
Yadavendra, S Chand - Multimedia Tools and Applications, 2022 - Springer
Deep learning methods are used to analyze satellite images. These satellite images contain
many constructed and natural objects, but these are not entirely visible and detectable with …
many constructed and natural objects, but these are not entirely visible and detectable with …
Joint multilayer spatial-spectral classification of hyperspectral images based on CNN and ConvLSTM
Joint Multilayer Spatial-Spectral Classification of Hyperspectral Images Based on CNN and
Convlstm Page 1 JOINT MULTILAYER SPATIAL-SPECTRAL CLASSIFICATION OF …
Convlstm Page 1 JOINT MULTILAYER SPATIAL-SPECTRAL CLASSIFICATION OF …
Artificial neural networks optimization and convolution neural networks to classifying images in remote sensing: A review
One of important functions of remote sensing data is producing the land-use/land-cover
maps. Image classification is one of important applications for remote sensing imaginary …
maps. Image classification is one of important applications for remote sensing imaginary …
Image based land cover classification for remote sensing applications-A review
MM Mishaa, AD Andrushia… - 2021 3rd International …, 2021 - ieeexplore.ieee.org
Land cover is a material present in the earth surface. It consists of forest, farming land, fertile,
infertile lands, desert, water bodies and agricultural areas etc., The basic need for capturing …
infertile lands, desert, water bodies and agricultural areas etc., The basic need for capturing …
Classification of land cover from Sentinel-2 imagery using supervised classification technique (preliminary study)
E Miranda, AB Mutiara… - 2018 International …, 2018 - ieeexplore.ieee.org
This paper intended to classify land cover of high-resolution satellite image using
supervised classification method. The object of this research was the land cover image of …
supervised classification method. The object of this research was the land cover image of …
Automated classification of remote sensing images using multileveled MobileNetV2 and DWT techniques
Automated classification of remote sensing images is one of the complex issues in robotics
and machine learning fields. Many models have been proposed for remote sensing image …
and machine learning fields. Many models have been proposed for remote sensing image …
Detection, localization and analysis of oil spills in water through wireless thermal imaging and spectrometer based intelligent system
In this study, a marine robotic system is designed to locate and to quantify the surface water
pollution in lakes and ponds with the consideration of the influences of neighboring …
pollution in lakes and ponds with the consideration of the influences of neighboring …