A Comparative Study of Machine Learning Techniques with Convolutional Neural Networks for Land Use Land Cover Classification

Key Points

• This research aims to compare various machine learning techniques, including convolutional neural networks, for classifying land use and land cover.
• Comparison of multiple machine learning techniques
• Utilization of convolutional neural networks
• Analysis of classification accuracy
• Evaluation of land use/land cover datasets
• Identified the most effective machine learning techniques
• Convolutional neural networks showed superior performance
• Demonstrated improved accuracy in land cover classification