Date of Award
Master of Science (MS)
Dr. Zhijun Qiao
Dr. Andras Balogh
Dr. Dambaru Bhatta
With the rapid development of artificial intelligence technology and the emergence of a large number of innovative theories, the concept of deep learning is widely used in object detection, speech recognition, language translation and other fields. One of the important practices is target recognition in SAR images. Although it shows certain effectiveness in some researches, when using deep learning algorithm, there are still many problems that have not yet been solved. For example, people do not have a good understanding of how convolution works and the impact of convolution on the algorithm, although convolution works well in the CNN algorithm.
This thesis aims at analyzing the influence of the convolution in CNN algorithm. The goal can be achieved by controlling the convolution kernels. By controlling the amount of convolution kernels and the corresponding padding, the influence of convolution kernels will be determined. Then, the correctness of the above theories will be explained by conducting experiments using the MSTAR database.
Zou, Ligang, "Analysis of the CNN Algorithm in Target Recognition by Using the MSTAR Database" (2019). Theses and Dissertations - UTRGV. 533.