Optimizing Target Recognition in Synthetic Aperture Radar Imagery: A Hyperparameter- Tuned Approach With Iterative Transfer Learning and Branched-Convolutional Neural Network

Optimizing Target Recognition in Synthetic Aperture Radar Imagery: A Hyperparameter- Tuned Approach With Iterative Transfer Learning and Branched-Convolutional Neural Network

Real-world deployment of Automatic Target Recognition (ATR) in Synthetic Aperture Radar (SAR) often faces challenges due to the computational demands of Convolutional Neural Networks (CNNs). This paper proposes an innovative solution, combining Iterative Transfer Learning (ITL) with a lightweight br...

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Bibliographic Details
Main Authors: Bileesh Plakkal Babu, Swathi Jamjala Narayanan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Automatic target recognition
computer vision
convolutional neural network
hyperparameter tuning
synthetic aperture radar
Online Access:https://ieeexplore.ieee.org/document/10443009/

Internet

https://ieeexplore.ieee.org/document/10443009/

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