期刊論文
| 學年 | 113 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2024-11-05 |
| 作品名稱 | Whale Optimization Algorithm with Machine Learning for Microwave Imaging |
| 作品名稱（其他語言） | |
| 著者 | Chien-Ching Chiu; Ching-Lieh Li; Po-Hsiang Chen; Hung-Ming Cheng; Hao Jiang |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Electronics (13)22, 4342 |
| 摘要 | This paper introduces a novel approach for reconstructing microwave imaging by combining the Whale Optimization Algorithm (WOA) with deep learning techniques. In it, electromagnetic waves are used to illuminate inhomogeneous dielectric objects in free space, and the scattered field is recorded. Due to the highly nonlinear nature of microwave imaging, the WOA is first employed to calculate an initial guess from the measured scattered field of dielectric objects. This step significantly reduces the training complexity for machine learning. Subsequently, the initial guess provided by the WOA is fed into a U-Net to accurately reconstruct the microwave image. Numerical simulation results indicate that the combination of the WOA and machine learning outperforms traditional methods under varying noise levels, enhancing the precision and effectiveness of the reconstruction process. In detail, the RMSE can be reduced 4–10% for dielectric constant distribution from 1 to 2.5 and SSIM can be increased about 30% for most cases. |
| 關鍵字 | whale optimization algorithm; electromagnetic sensing; U-Net; electromagnetic imaging |
| 語言 | en_US |
| ISSN | 2079-9292 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 是 |
| 國別 | USA |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/127510 ) |