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

B V Pushpalatha; Mallikarjuna P. B; H N Mahendra; Radheshyam Rai

doi:10.1504/ijids.2027.10076835

March 6, 2026International Journal of Information and Decision Sciences

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

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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

Implication

A comparative analysis identifies effective machine learning techniques for land cover classification, suggesting optimal methods for environmental applications.

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Cite This Study

Pushpalatha et al. (2026) studied this question.

synapsesocial.com/papers/69ada836bc08abd80d5bb562 https://doi.org/10.1504/ijids.2027.10076835

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

Key Points

Implication

Abstract

Discussion

Cite This Study

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

Key Points

Implication

Abstract

Discussion

Cite This Study

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