Comparison of machine learning classifiers for land cover changes using google earth engine

S Mangkhaseum, A Hanazawa - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Increasing urbanization causes a variety of environmental changes, not only in regional but
in the global scale, especially in developing countries. The developing countries like Lao …

Digital and geographical feature detection by machine learning techniques using google earth engine for CPEC traffic management

S Mazhar, G Sun, A Bilal, Y Li… - Wireless …, 2022 - Wiley Online Library
The center of human settlements is in the cities, which must have high‐quality habitats for
their inhabitants. Many megachallenges of urbanization, population development, global …

Application of convolutional neural network in classification of high resolution agricultural remote sensing images

C Yao, Y Zhang, H Liu - The international archives of …, 2017 - isprs-archives.copernicus.org
With the rapid development of Precision Agriculture (PA) promoted by high-resolution
remote sensing, it makes significant sense in management and estimation of agriculture …

Remote sensing image classification based on convolutional neural networks

MA Shafaey, MAM Salem, MN Al-Berry… - … Conference on Artificial …, 2020 - Springer
Nowadays, large amounts of high resolution remote-sensing images are acquired daily.
However, the satellite image classification is requested for many applications such as …

Deep learning models for inventory of agriculture crops and yield production using satellite images

HN Mahendra, S Mallikarjunaswamy… - 2022 IEEE 2nd …, 2022 - ieeexplore.ieee.org
Cropland mapping and classification is one of the vital steps in agricultural for planning and
management activities at large and small scales. Crop mapping plays an important role in …

Multi-level feature extraction for automated land cover classification using deep cnn with long short-term memory network

S Patel, N Ganatra, R Patel - 2022 6th International …, 2022 - ieeexplore.ieee.org
In remote sensing and satellite imagery, classification of land cover usage are the vital tasks
that help to understand about the physical aspects of the surface of the Earth and its …

Machine learning-based smart surveillance and intrusion detection system for national geographic borders

M Sharma, CRS Kumar - … : Select Proceedings of ICRTAC-AIT 2020, 2021 - Springer
The safety, security and unmanned surveillance of national geographic borders of the
country is of supreme importance. Greater security measures and surveillance techniques …

Smart city technologies, key components, and its aspects

UT Khan, MF Zia - 2021 International Conference on Innovative …, 2021 - ieeexplore.ieee.org
Urban Population is rapidly increasing, which is creating city management problems. The
smart city provides solutions to the problems that are arising due to rapid urbanization. The …

Agriculture monitoring system based on internet of things by deep learning feature fusion with classification

KS Kumari, SLA Haleem, G Shivaprakash… - Computers and …, 2022 - Elsevier
This research proposed novel technique in crop monitoring system using machine learning-
based classification using UAV. To monitor and operate activities from remote locations …

[PDF][PDF] Onion Crop Monitoring with Multispectral Imagery Using Deep Neural Network

NU Din, B Naz, S Zai, W Ahmed - International Journal of …, 2021 - pdfs.semanticscholar.org
The world's growing population leads the government of Pakistan to increase the supply of
food for the coming years in a well-organized manner. Feasible agriculture plays a vital role …