Automatic target detection and recognition of military vehicles in synthetic aperture radar images is fostered by optimizing VGG-googLeNet with the giraffe kicking optimization algorithm

Author:

Shakin Banu A.,Shahul Hameed K. A.

Publisher

Springer Science and Business Media LLC

Reference43 articles.

1. Pawar, S., Gandhe, S.: SAR (Synthetic Aperture Radar) image study and analysis for object recognition in surveillance. IJISAE 11, 552–573 (2023)

2. Ukwuoma, C.C., Zhiguang, Q., Tienin, B.W., Yussif, S.B., Ejiyi, C.J., Urama, G.C., Chikwendu, I.A.: Synthetic aperture radar automatic target recognition based on a simple attention mechanism. Int. J. Interact. Multimed. Artif. Intell. 8(4), 67 (2023)

3. Geng, Z., Xu, Y., Wang, B.N., Yu, X., Zhu, D.Y., Zhang, G.: Target recognition in SAR images by deep learning with training data augmentation. Sensors 23(2), 941 (2023)

4. Arora, N., Kumar, Y., Karkra, R., Kumar, M.: Automatic vehicle detection system in different environment conditions using fast R-CNN. Multimed. Tools Appl. 81(13), 18715–18735 (2022)

5. Wang, Z., Zhan, J., Li, Y., Zhong, Z., Cao, Z.: A new scheme of vehicle detection for severe weather based on multi-sensor fusion. Measurement 191, 110737 (2022)

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