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Target Classification in Synthetic Aperture Radar Images Using Quantized Wavelet Scattering Networks †
The need to classify targets and features in high-resolution imagery is of interest in applications such as detection of landmines in ground penetrating radar and tumors in medical ultrasound images. Convolutional neural networks (CNNs) trained using extensive datasets are being investigated recentl...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8348969/ https://www.ncbi.nlm.nih.gov/pubmed/34372219 http://dx.doi.org/10.3390/s21154981 |