B. Chellapraba1,*, D. Manohari2, K. Periyakaruppan3, M. S. Kavitha4
Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2353-2366, 2023, DOI:10.32604/iasc.2023.029923
Abstract Hyperspectral (HS) image classification is a hot research area due to challenging issues such as existence of high dimensionality, restricted training data, etc. Precise recognition of features from the HS images is important for effective classification outcomes. Additionally, the recent advancements of deep learning (DL) models make it possible in several application areas. In addition, the performance of the DL models is mainly based on the hyperparameter setting which can be resolved by the design of metaheuristics. In this view, this article develops an automated red deer algorithm with deep learning enabled hyperspectral image (HSI) classification (RDADL-HIC) technique. The proposed… More >
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