Machine learning is a powerful tool that may significantly improve the judgment of businesses and individuals alike. The use of machine learning methods in data analytics is now commonplace, especially with the development of data science. Identifying enemy fighter planes is crucial for military applications, as it plays a role in operational planning. The challenge is in correctly determining the orientation of the unknown airplane. The 30 different types of aircraft in this database were retrieved from the Kaggle repository. An 80:20 or 70:30 split of the image database was used to create a training set and test set, respectively. The normalized feature sets allowed the LSTM, CNN, BiLSTM, ANN, Autoencoder, and Hybrid Model deep learning models to be developed and trained to their full potential. The test aircraft image was fed into the hybrid deep neural networks so that they could be categorized. The developed automatic aircraft image identification system achieved a classification accuracy of 98.85%.


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    Title :

    Enhancing Military Surveillance: Advanced Aircraft Image Identification using Hybrid Deep Neural Networks




    Publication date :

    2023-12-11


    Size :

    1364805 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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