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Transferring Synthetic Elementary Learning Tasks to Classification of Complex Targets
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019)
Deep learning has a promising impact on target classification performance at the expense of huge training data requirements. Therefore, the use of simulated data is inevitable for convergence of deep models (DMs). However, ...
Utilizing Resonant Scattering Signal Characteristics of Magnetic Spheres via Deep Learning for Improved Target Classification
(IEEE, 2019)
Object classification using LAte-time Resonant Scattering Electromagnetic Signals (LARSESs) is a significant problem found in different areas of application. Due to their special properties, spherical objects play an ...
Utilizing Resonant Scattering Signal Characteristics of Magnetic Spheres via Deep Learning for Improved Target Classification
(2019 International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2019, 2019)
Object classification using LAte-time Resonant Scattering Electromagnetic Signals (LARSESs) is a significant problem found in different areas of application. Due to their special properties, spherical objects play an ...
Transferring Synthetic Elementary Learning Tasks to Classification of Complex Targets
(IEEE Antennas and Wireless Propagation Letters, 2019)
Deep learning has a promising impact on target classification performance at the expense of huge training data requirements. Therefore, the use of simulated data is inevitable for convergence of deep models (DMs). However, ...
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