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  • Open Access

    ARTICLE

    Masked Autoencoders as Single Object Tracking Learners

    Chunjuan Bo1,*, Xin Chen2, Junxing Zhang1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1105-1122, 2024, DOI:10.32604/cmc.2024.052329

    Abstract Significant advancements have been witnessed in visual tracking applications leveraging ViT in recent years, mainly due to the formidable modeling capabilities of Vision Transformer (ViT). However, the strong performance of such trackers heavily relies on ViT models pretrained for long periods, limiting more flexible model designs for tracking tasks. To address this issue, we propose an efficient unsupervised ViT pretraining method for the tracking task based on masked autoencoders, called TrackMAE. During pretraining, we employ two shared-parameter ViTs, serving as the appearance encoder and motion encoder, respectively. The appearance encoder encodes randomly masked image data,… More >

  • Open Access

    ARTICLE

    SMSTracker: A Self-Calibration Multi-Head Self-Attention Transformer for Visual Object Tracking

    Zhongyang Wang, Hu Zhu, Feng Liu*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 605-623, 2024, DOI:10.32604/cmc.2024.050959

    Abstract Visual object tracking plays a crucial role in computer vision. In recent years, researchers have proposed various methods to achieve high-performance object tracking. Among these, methods based on Transformers have become a research hotspot due to their ability to globally model and contextualize information. However, current Transformer-based object tracking methods still face challenges such as low tracking accuracy and the presence of redundant feature information. In this paper, we introduce self-calibration multi-head self-attention Transformer (SMSTracker) as a solution to these challenges. It employs a hybrid tensor decomposition self-organizing multi-head self-attention transformer mechanism, which not only… More >

  • Open Access

    REVIEW

    Maximum Power Point Tracking Technology for PV Systems: Current Status and Perspectives

    Bo Yang1,2, Rui Xie1, Zhengxun Guo3,4,*

    Energy Engineering, Vol.121, No.8, pp. 2009-2022, 2024, DOI:10.32604/ee.2024.049423

    Abstract Maximum power point tracking (MPPT) technology plays a key role in improving the energy conversion efficiency of photovoltaic (PV) systems, especially when multiple local maximum power points (LMPPs) occur under partial shading conditions (PSC). It is necessary to modify the operating point efficiently and accurately with the help of MPPT technology to maximize the collected power. Even though a lot of research has been carried out and impressive progress achieved for MPPT technology, it still faces some challenges and dilemmas. Firstly, the mathematical model established for PV cells is not precise enough. Second, the existing… More > Graphic Abstract

    Maximum Power Point Tracking Technology for PV Systems: Current Status and Perspectives

  • Open Access

    ARTICLE

    Investigation of Inside-Out Tracking Methods for Six Degrees of Freedom Pose Estimation of a Smartphone in Augmented Reality

    Chanho Park1, Takefumi Ogawa2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3047-3065, 2024, DOI:10.32604/cmc.2024.048901

    Abstract Six degrees of freedom (6DoF) input interfaces are essential for manipulating virtual objects through translation or rotation in three-dimensional (3D) space. A traditional outside-in tracking controller requires the installation of expensive hardware in advance. While inside-out tracking controllers have been proposed, they often suffer from limitations such as interaction limited to the tracking range of the sensor (e.g., a sensor on the head-mounted display (HMD)) or the need for pose value modification to function as an input interface (e.g., a sensor on the controller). This study investigates 6DoF pose estimation methods without restricting the tracking… More >

  • Open Access

    ARTICLE

    A Layered Energy-Efficient Multi-Node Scheduling Mechanism for Large-Scale WSN

    Xue Zhao, Shaojun Tao, Hongying Tang, Jiang Wang*, Baoqing Li*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1335-1351, 2024, DOI:10.32604/cmc.2024.047996

    Abstract In recent years, target tracking has been considered one of the most important applications of wireless sensor network (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally critical objectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. The proposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH) election, pre-selection, and task set selection mechanisms, where the latter two kinds of selections form a two-layer selection mechanism. The CH election innovatively introduces the movement trend of the target and establishes a scoring mechanism to determine More >

  • Open Access

    ARTICLE

    Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

    Asifa Mehmood Qureshi1, Naif Al Mudawi2, Mohammed Alonazi3, Samia Allaoua Chelloug4, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3683-3701, 2024, DOI:10.32604/cmc.2024.043611

    Abstract Road traffic monitoring is an imperative topic widely discussed among researchers. Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides. However, aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area. To this end, different models have shown the ability to recognize and track vehicles. However, these methods are not mature enough to produce accurate results in complex road scenes. Therefore, this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with… More >

  • Open Access

    ARTICLE

    Research on the MPPT of Photovoltaic Power Generation Based on Improved WOA and P&O under Partial Shading Conditions

    Jian Zhong, Lei Zhang*, Ling Qin

    Energy Engineering, Vol.121, No.4, pp. 951-971, 2024, DOI:10.32604/ee.2023.041433

    Abstract Partial shading conditions (PSCs) caused by uneven illumination become one of the most common problems in photovoltaic (PV) systems, which can make the PV power-voltage (P-V) characteristics curve show multi-peaks. Traditional maximum power point tracking (MPPT) methods have shortcomings in tracking to the global maximum power point (GMPP), resulting in a dramatic decrease in output power. In order to solve the above problems, intelligent algorithms are used in MPPT. However, the existing intelligent algorithms have some disadvantages, such as slow convergence speed and large search oscillation. Therefore, an improved whale algorithm (IWOA) combined with the More >

  • Open Access

    ARTICLE

    A New Flower Pollination Algorithm Strategy for MPPT of Partially Shaded Photovoltaic Arrays

    Muhannad J. Alshareef*

    Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 297-313, 2023, DOI:10.32604/iasc.2023.046722

    Abstract Photovoltaic (PV) systems utilize maximum power point tracking (MPPT) controllers to optimize power output amidst varying environmental conditions. However, the presence of multiple peaks resulting from partial shading poses a challenge to the tracking operation. Under partial shade conditions, the global maximum power point (GMPP) may be missed by most traditional maximum power point tracker. The flower pollination algorithm (FPA) and particle swarm optimization (PSO) are two examples of metaheuristic techniques that can be used to solve the issue of failing to track the GMPP. This paper discusses and resolves all issues associated with using… More >

  • Open Access

    ARTICLE

    Enhancing Identity Protection in Metaverse-Based Psychological Counseling System

    Jun Lee1, Hanna Lee2, Seong Chan Lee2, Hyun Kwon3,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 617-632, 2024, DOI:10.32604/cmc.2023.045768

    Abstract Non-face-to-face psychological counseling systems rely on network technologies to anonymize information regarding client identity. However, these systems often face challenges concerning voice data leaks and the suboptimal communication of the client’s non-verbal expressions, such as facial cues, to the counselor. This study proposes a metaverse-based psychological counseling system designed to enhance client identity protection while ensuring efficient information delivery to counselors during non-face-to-face counseling. The proposed system incorporates a voice modulation function that instantly modifies/masks the client’s voice to safeguard their identity. Additionally, it employs real-time client facial expression recognition using an ensemble of decision… More >

  • Open Access

    CORRECTION

    Correction: Spatio Temporal Tourism Tracking System Based on Adaptive Convolutional Neural Network

    L. Maria Michael Visuwasam1,*, D. Paul Raj2

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 267-267, 2024, DOI:10.32604/csse.2023.047461

    Abstract This article has no abstract. More >

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