Sep 1, 2023 · The aim of this research is to develop a system to precisely classify FHSS signals in a multisignal environment. Hence, this work proposes a ...
Sep 1, 2023 · A hybrid convolutional neural network (HCNN) system with the fusion of handcrafted and deep features is developed in this paper for the FHSS ...
The CNN is used as a deep feature extractor by transforming the intermediate frequency signal to the time-frequency representation and used as a two-dimensional ...
A hybrid convolutional neural network with fusion of handcrafted and deep features for FHSS signals classification. https://doi.org/10.1016/j.eswa ...
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A Hybrid Convolutional Neural Network with Fusion of Handcrafted and Deep Features for FHSS Signals Classification. MT Khan, UU Sheikh. Expert Systems with ...
Sep 20, 2023 · In this research, a hybrid convolutional neural network (HCNN) system with the fusion of handcrafted and deep features is proposed to classify FHSS signals.
Jul 4, 2023 · This section discusses the performance of the XGBoost and DT algorithms with the fused features of the DL networks for diagnosing malignant lymphomas.
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Apr 12, 2024 · Therefore, in this study, a modified convolutional neural network (MCNN) with rectangular filters is proposed to classify FHSS signals, with a ...
May 23, 2024 · In this research, a hybrid convolutional neural network (HCNN) system with the fusion of handcrafted and deep features is proposed to classify ...
Mar 8, 2024 · The HCNN system involves the fusion of both handcrafted and deep features. The CNN functions as a deep feature extractor, converting the ...