Performance of the extended maximum average correlation height (EMACH) filter and the polynomial distance classifier correlation filter (PDCCF) for multiclass SAR detection and classification

By R. Singh, B. V. Vijaya Kumar. SPIE Defense + Commercial Sensing, 2002

49 citations recorded by the source corpus.

Subfields: Aerospace Engineering

View Paper: https://www.semanticscholar.org/paper/64574b4a233c3a8db69bf9b8e9c76b384d679284

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In Aerospace Engineering

1. Feng Xu
2. Haipeng Wang
3. Yaqiu Jin
4. Sizhe Chen
5. Jianwei Ma
6. Siwei Yu
7. Mohammad Rostami
8. Lichao Mou

Citations in the corpus

• Target Classification Using the Deep Convolutional Networks for SAR Images (2016, methodology): “These methods include extended maximum average correlation height (EMACH) [29], SVM [9], conditional Gaussian model (Cond Gauss) [30], AdaBoost [10], iterative graph thickening (IGT) [31], sparse representation of monogenic signal (MSRC) [32], monogenic scale space (MSS) [33], and modified po-”