Ying Tian^{1, *}, Libing Wang¹, Hexin Gu², Lin Fan³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2397-2412, 2020, DOI:10.32604/cmc.2020.011386

Abstract The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space.… More >

Jianzhong Qi^{1, 2, *}, Qingping Song³, Jim Feng⁴

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2385-2396, 2020, DOI:10.32604/cmc.2020.011651

Abstract The area navigation system, discussed in this paper, is composed of ground responders and a navigation terminal and can position a high-velocity aircraft and measure its velocity. This navigation system is silent at ordinary times. It sends out a request signal when positioning is required for an aircraft, and then the ground responders send a signal for resolving the aircraft. Combining the direct sequence spread spectrum and frequency hopping, the concealed communication mode is used in the whole communication process, with short communication pulses as much as possible, so the system has strong concealment and anti-interference characteristics. As the transmission… More >

Jin Wang^{1, 2}, Wencheng Chen¹, Lei Wang^{3, *}, R. Simon Sherratt⁴, Osama Alfarraj⁵, Amr Tolba^{5, 6}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2365-2384, 2020, DOI:10.32604/cmc.2020.011567

Abstract As the number of sensor network application scenarios continues to grow, the security problems inherent in this approach have become obstacles that hinder its wide application. However, it has attracted increasing attention from industry and academia. The blockchain is based on a distributed network and has the characteristics of nontampering and traceability of block data. It is thus naturally able to solve the security problems of the sensor networks. Accordingly, this paper first analyzes the security risks associated with data storage in the sensor networks, then proposes using blockchain technology to ensure that data storage in the sensor networks is… More >

Zhenli Wang^{1, *}, Qun Wang¹, Jiayin Liu¹, Zheng Liang¹, Jingsong Xu²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2351-2363, 2020, DOI:10.32604/cmc.2020.011909

Abstract To address the low-resolution imaging problem in relation to traditional Range Doppler (RD) algorithm, this paper intends to propose a new algorithm based on Fractional Fourier Transform (FrFT), which proves highly advantageous in the acquisition of high-resolution Synthetic Aperture Radar (SAR) images. The expression of the optimal order of SAR range signals using FrFT is deduced in detail, and the corresponding expression of the azimuth signal is also given. Theoretical analysis shows that, the optimal order in range (azimuth) direction, which turns out to be very unique, depends on the known imaging parameters of SAR, therefore the engineering practicability of… More >

Rong Duan¹, Junshan Tan^{1, *}, Jiaohua Qin¹, Xuyu Xiang¹, Yun Tan¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2335-2350, 2020, DOI:10.32604/cmc.2020.012161

Abstract In recent years, with the massive growth of image data, how to match the image required by users quickly and efficiently becomes a challenge. Compared with single-view feature, multi-view feature is more accurate to describe image information. The advantages of hash method in reducing data storage and improving efficiency also make us study how to effectively apply to large-scale image retrieval. In this paper, a hash algorithm of multi-index image retrieval based on multi-view feature coding is proposed. By learning the data correlation between different views, this algorithm uses multi-view data with deeper level image semantics to achieve better retrieval… More >

Panyu Liu¹, Huilin Ren², Xiaojun Shi³, Yangyang Li^{4, *}, Zhiping Cai¹, Fang Liu⁵, Huacheng Zeng⁶

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2321-2334, 2020, DOI:10.32604/cmc.2020.010522

Abstract Deep learning technology has been widely used in computer vision, speech recognition, natural language processing, and other related fields. The deep learning algorithm has high precision and high reliability. However, the lack of resources in the edge terminal equipment makes it difficult to run deep learning algorithms that require more memory and computing power. In this paper, we propose MoTransFrame, a general model processing framework for deep learning models. Instead of designing a model compression algorithm with a high compression ratio, MoTransFrame can transplant popular convolutional neural networks models to resources-starved edge devices promptly and accurately. By the integration method,… More >

Cong Wang¹, Mingming Zhao², Qinyue Wang^{2, 3}, Min Li^{2, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2309-2319, 2020, DOI:10.32604/cmc.2020.09958

Abstract This paper introduces a novel mechanism to improve the performance of peer assessment for collaborative learning. Firstly, a small set of assignments which have being pre-scored by the teacher impartially, are introduced as “sentinels”. The reliability of a reviewer can be estimated by the deviation between the sentinels’ scores judged by the reviewers and the impartial scores. Through filtering the inferior reviewers by the reliability, each score can then be subjected into mean value correction and standard deviation correction processes sequentially. Then the optimized mutual score which mitigated the influence of the subjective differences of the reviewers are obtained. We… More >

Huaixi Xing¹, Yu Zhao¹, Yuhui Zhang¹, You Chen^{1, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2295-2308, 2020, DOI:10.32604/cmc.2020.011858

Abstract Aiming at the yaw problem caused by inertial navigation system errors accumulation during the navigation of an intelligent aircraft, a three-dimensional trajectory planning method based on the particle swarm optimization-A star (PSO-A*) algorithm is designed. Firstly, an environment model for aircraft error correction is established, and the trajectory is discretized to calculate the positioning error. Next, the positioning error is corrected at many preset trajectory points. The shortest trajectory and the fewest correction times are regarded as optimization goals to improve the heuristic function of A star (A*) algorithm. Finally, the index weights are continuously optimized by the particle swarm… More >

Yong Wu¹, Binjun Wang^{1, *}, Wei Li²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2277-2294, 2020, DOI:10.32604/cmc.2020.011609

Abstract Graph convolutional networks (GCNs) have been developed as a general and powerful tool to handle various tasks related to graph data. However, current methods mainly consider homogeneous networks and ignore the rich semantics and multiple types of objects that are common in heterogeneous information networks (HINs). In this paper, we present a Heterogeneous Hyperedge Convolutional Network (HHCN), a novel graph convolutional network architecture that operates on HINs. Specifically, we extract the rich semantics by different metastructures and adopt hyperedge to model the interactions among metastructure-based neighbors. Due to the powerful information extraction capabilities of metastructure and hyperedge, HHCN has the… More >

Weijin Jiang^{1, 2, 3, 4}, Fang Ye^{1, 2, *}, Wei Liu^{2, 3}, Xiaoliang Liu^{1, 2}, Guo Liang⁵, Yuhui Xu^{2, 3}, Lina Tan^{1, 2}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2263-2275, 2020, DOI:10.32604/cmc.2020.010082

Abstract With the rapid development of information technology, the explosive growth of data information has become a common challenge and opportunity. Social network services represented by WeChat, Weibo and Twitter, drive a large amount of information due to the continuous spread, evolution and emergence of users through these platforms. The dynamic modeling, analysis, and network information prediction, has very important research and application value, and plays a very important role in the discovery of popular events, personalized information recommendation, and early warning of bad information. For these reasons, this paper proposes an adaptive prediction algorithm for network information transmission. A popularity… More >