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  • Open Access

    ARTICLE

    Recognition and Tracking of Objects in a Clustered Remote Scene Environment

    Haris Masood1, Amad Zafar2, Muhammad Umair Ali3, Muhammad Attique Khan4, Salman Ahmed1, Usman Tariq5, Byeong-Gwon Kang6, Yunyoung Nam6,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1699-1719, 2022, DOI:10.32604/cmc.2022.019572

    Abstract Object recognition and tracking are two of the most dynamic research sub-areas that belong to the field of Computer Vision. Computer vision is one of the most active research fields that lies at the intersection of deep learning and machine vision. This paper presents an efficient ensemble algorithm for the recognition and tracking of fixed shape moving objects while accommodating the shift and scale invariances that the object may encounter. The first part uses the Maximum Average Correlation Height (MACH) filter for object recognition and determines the bounding box coordinates. In case the correlation based MACH filter fails, the algorithms… More >

  • Open Access

    ARTICLE

    Enhancing the Robustness of Visual Object Tracking via Style Transfer

    Abdollah Amirkhani1,*, Amir Hossein Barshooi1, Amir Ebrahimi2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 981-997, 2022, DOI:10.32604/cmc.2022.019001

    Abstract The performance and accuracy of computer vision systems are affected by noise in different forms. Although numerous solutions and algorithms have been presented for dealing with every type of noise, a comprehensive technique that can cover all the diverse noises and mitigate their damaging effects on the performance and precision of various systems is still missing. In this paper, we have focused on the stability and robustness of one computer vision branch (i.e., visual object tracking). We have demonstrated that, without imposing a heavy computational load on a model or changing its algorithms, the drop in the performance and accuracy… More >

  • Open Access

    ARTICLE

    An Ensemble Learning Based Approach for Detecting and Tracking COVID19 Rumors

    Sultan Noman Qasem1,2, Mohammed Al-Sarem3,4, Faisal Saeed3,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1721-1747, 2022, DOI:10.32604/cmc.2022.018972

    Abstract Rumors regarding epidemic diseases such as COVID 19, medicines and treatments, diagnostic methods and public emergencies can have harmful impacts on health and political, social and other aspects of people’s lives, especially during emergency situations and health crises. With huge amounts of content being posted to social media every second during these situations, it becomes very difficult to detect fake news (rumors) that poses threats to the stability and sustainability of the healthcare sector. A rumor is defined as a statement for which truthfulness has not been verified. During COVID 19, people found difficulty in obtaining the most truthful news… More >

  • Open Access

    ARTICLE

    Deep Learning with Backtracking Search Optimization Based Skin Lesion Diagnosis Model

    C. S. S. Anupama1, L. Natrayan2, E. Laxmi Lydia3, Abdul Rahaman Wahab Sait4, José Escorcia-Gutierrez5, Margarita Gamarra6,*, Romany F. Mansour7

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1297-1313, 2022, DOI:10.32604/cmc.2022.018396

    Abstract Nowadays, quality improvement and increased accessibility to patient data, at a reasonable cost, are highly challenging tasks in healthcare sector. Internet of Things (IoT) and Cloud Computing (CC) architectures are utilized in the development of smart healthcare systems. These entities can support real-time applications by exploiting massive volumes of data, produced by wearable sensor devices. The advent of evolutionary computation algorithms and Deep Learning (DL) models has gained significant attention in healthcare diagnosis, especially in decision making process. Skin cancer is the deadliest disease which affects people across the globe. Automatic skin lesion classification model has a highly important application… More >

  • Open Access

    ARTICLE

    Energy Saving Control Approach for Trajectory Tracking of Autonomous Mobile Robots

    Yung-Hsiang Chen1, Yung-Yue Chen2, Shi-Jer Lou3, Chiou-Jye Huang4,*

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 357-372, 2022, DOI:10.32604/iasc.2022.018663

    Abstract This research presents an adaptive energy-saving H2 closed-form control approach to solve the nonlinear trajectory tracking problem of autonomous mobile robots (AMRs). The main contributions of this proposed design are as follows: closed-form approach, simple structure of the control law, easy implementation, and energy savings through trajectory tracking design of the controlled AMRs. It is difficult to mathematically obtained this adaptive H2 closed-form solution of AMRs. Therefore, through a series of mathematical analyses of the trajectory tracking error dynamics of the controlled AMRs, the trajectory tracking problem of AMRs can be transformed directly into a solvable problem, and an adaptive… More >

  • Open Access

    ARTICLE

    Adaptive Object Tracking Discriminate Model for Multi-Camera Panorama Surveillance in Airport Apron

    Dequan Guo1, Qingshuai Yang2, Yu-Dong Zhang3, Gexiang Zhang1, Ming Zhu1, Jianying Yuan1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 191-205, 2021, DOI:10.32604/cmes.2021.016347

    Abstract Autonomous intelligence plays a significant role in aviation security. Since most aviation accidents occur in the take-off and landing stage, accurate tracking of moving object in airport apron will be a vital approach to ensure the operation of the aircraft safely. In this study, an adaptive object tracking method based on a discriminant is proposed in multi-camera panorama surveillance of large-scale airport apron. Firstly, based on channels of color histogram, the pre-estimated object probability map is employed to reduce searching computation, and the optimization of the disturbance suppression options can make good resistance to similar areas around the object. Then… More >

  • Open Access

    ARTICLE

    GPS Vector Tracking Receivers with Rate Detector for Integrity Monitoring

    Dah-Jing Jwo*, Ming-Hsuan Lee

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2387-2403, 2021, DOI:10.32604/cmc.2021.018670

    Abstract In this paper, the integrity monitoring algorithm based on a Kalman filter (KF) based rate detector is employed in the vector tracking loop (VTL) of the Global Positioning System (GPS) receiver. In the VTL approach, the extended Kalman filter (EKF) simultaneously tracks the received signals and estimates the receiver’s position, velocity, etc. In contrast to the scalar tracking loop (STL) that uses the independent parallel tracking loop approach, the VTL technique uses the correlation of each satellite signal and user dynamics and thus reduces the risk of loss lock of signals. Although the VTL scheme provides several important advantages, the… More >

  • Open Access

    ARTICLE

    The Impact of a Bicuspid Aortic Valve on Aortic Geometry and Function in Patients with Aortic Coarctation: A Comprehensive CMR Study

    Laura Schweikert1, Dominik Gabbert1, Sylvia Krupickova2, Inga Voges1,*

    Congenital Heart Disease, Vol.16, No.6, pp. 551-560, 2021, DOI:10.32604/CHD.2021.016635

    Abstract Background: An isolated bicuspid aortic valve (BAV) is associated with structural and functional abnormalities of the aorta and the left ventricle (LV). Although ~50% of patients with aortic coarctation (CoA) have a BAV, less is known about its impact on LV function and aortic geometry and function in CoA patients. In this cardiovascular magnetic resonance imaging (CMR) study, we analysed markers of LV and aortic function as well as aortic geometry in a large cohort of CoA patients with a BAV and compared them with CoA patients with a tricuspid aortic valve (TAV). Methods: We included 48 patients with a… More >

  • Open Access

    ARTICLE

    SVSF-Based Robust UGV/UAV Control/Tracking Architecture in Disturbed Environment

    Abdelatif Oussar1,*, Abdelmoumen Ferrag1, Mohamed Guiatni1, Mustapha Hamerlain2

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 467-495, 2021, DOI:10.32604/iasc.2021.01000

    Abstract This paper presents the design of a robust architecture for the tracking of an unmanned ground vehicle (UGV) by an unmanned aerial vehicle (UAV). To enhance the robustness of the ground vehicle in the face of external disturbances and handle the non-linearities due to inputs saturation, an integral sliding mode controller was designed for the task of trajectory tracking. Stabilization of the aerial vehicle is achieved using an integral-backstepping solution. Estimation of the relative position between the two agents was solved using two approaches: the first solution (optimal) is based on a Kalman filter (KF) the second solution (robust) uses… More >

  • Open Access

    ARTICLE

    Support Vector Machine Assisted GPS Navigation in Limited Satellite Visibility

    Dah-Jing Jwo*, Jia-Chyi Wu, Kuan-Lin Ho

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 555-574, 2021, DOI:10.32604/cmc.2021.018320

    Abstract This paper investigates performance improvement via the incorporation of the support vector machine (SVM) into the vector tracking loop (VTL) for the Global Positioning System (GPS) in limited satellite visibility. Unlike the traditional scalar tracking loop (STL), the tracking and navigation modules in the VTL are not independent anymore since the user’s position can be determined by using the information from other satellites and can be predicted on the basis of the states of the user. The method proposed in this paper makes use of the SVM to bridge the GPS signal and prevent the error growth due to signal… More >

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