Lilan Zou¹, Bo Liang¹, Xu Cheng², Shufa Li^1,*, Cong Lin^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2641-2659, 2023, DOI:10.32604/cmes.2023.028037

Abstract Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment. In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment, we proposed a more effective and robust target detection framework based on deep learning, which can make full use of the acoustic shadow information in the forward-looking sonar images to assist underwater target detection. Firstly, the weighted box fusion method is adopted to generate a fusion box by weighted fusion of prediction boxes with… More > Graphic Abstract

Yingying Chen¹, Weiqiang Tan², Shidang Li^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2675-2691, 2023, DOI:10.32604/cmes.2023.028533

Abstract In this paper, a novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless information and power transfer (SWIPT) aided sensor networks is developed for active beamforming of multiantenna transmitter and passive beamforming at intelligent reflecting surfaces (IRS). By optimizing the active beamformer assignment at the transmitter in conjunction with the passive beamformer assignment at the IRS, we aim to maximize the minimum harvested energy efficiency among all the energy receivers (ER) where information receivers (IR) are bound to the signal-interference-noise-ratio (SINR) and the maximum transmitted power of the transmitter. To handle the non-convex problem, both semi-definite relaxation (SDR) and… More >

Shixin Tu, Yuanyuan Jia, Jinglong Du^*, Baoru Han^*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 293-321, 2023, DOI:10.32604/cmes.2023.022308

Abstract The field of healthcare is considered to be the most promising application of intelligent sensor networks. However, the security and privacy protection of medical images collected by intelligent sensor networks is a hot problem that has attracted more and more attention. Fortunately, digital watermarking provides an effective method to solve this problem. In order to improve the robustness of the medical image watermarking scheme, in this paper, we propose a novel zero-watermarking algorithm with the integer wavelet transform (IWT), Schur decomposition and image block energy. Specifically, we first use IWT to extract low-frequency information and divide them into non-overlapping blocks,… More >