Microwave Imaging of Uniaxial Objects Using a Hybrid Input U-Net
學年 113
學期 2
出版（發表）日期 2025-04-17
作品名稱 Microwave Imaging of Uniaxial Objects Using a Hybrid Input U-Net
作品名稱（其他語言）
著者 Wei-Tsong Lee; Chien-Ching Chiu; Po-Hsiang Chen; Hung-Ming Cheng; Eng Hock Lim
單位
出版者
著錄名稱、卷期、頁數 Electronics 14(8), p.1633
摘要 This paper introduces hybrid inputs using Internet of Things (IoT) sensors for reconstructing microwave images of uniaxial objects. Specifically, scattered field data is obtained through IoT sensors, and artificial intelligence techniques are employed to enable real-time electromagnetic imaging. The presented method combines a U-Net architecture with an integrated input to reconstruct high-resolution images of dielectric targets for both Transverse Magnetic (TM) and Transverse Electric (TE) waves. The z-axial dielectric constants are reconstructed by the TM wave illumination, while the x- and y-axial dielectric constants are recovered by the TE wave illumination. First, a Direct Sampling Method (DSM) gives spatial details of the target. Second, a Back-propagation (BP) scheme provides basic information about the target’s properties. Lastly, we combine these two inputs by taking their product, which is further processed in the U-Net. Numerical results show that this integration can improve image quality with nearly no additional computing burden. Experiments also reveal that our proposed method is both accurate and efficient for uniaxial objects, making it a reliable solution to overcome the challenges in electromagnetic imaging.
關鍵字 internet of things sensors; U-Net; direct sampling method; back-propagation scheme; uniaxial objects; hybrid inputs
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 Chien Ching Chiu
審稿制度 是
國別 CHE
公開徵稿
出版型式 ,電子版,紙本
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機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/127670 )

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