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  • Open Access

    ARTICLE

    SlowFast Based Real-Time Human Motion Recognition with Action Localization

    Gyu-Il Kim1, Hyun Yoo2, Kyungyong Chung3,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2135-2152, 2023, DOI:10.32604/csse.2023.041030

    Abstract Artificial intelligence is increasingly being applied in the field of video analysis, particularly in the area of public safety where video surveillance equipment such as closed-circuit television (CCTV) is used and automated analysis of video information is required. However, various issues such as data size limitations and low processing speeds make real-time extraction of video data challenging. Video analysis technology applies object classification, detection, and relationship analysis to continuous 2D frame data, and the various meanings within the video are thus analyzed based on the extracted basic data. Motion recognition is key in this analysis. Motion recognition is a challenging… More >

  • Open Access

    Analysis of Subcellular Localization and Pathogenicity of Plum Bark Necrosis Stem-Pitting Associated Virus Protein P6

    Yuanyuan Li1,#, Jinze Mu2,#, Qingliang Li1, Huabing Liu3, Xuefeng Yuan2,*, Deya Wang1,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.7, pp. 2079-2085, 2023, DOI:10.32604/phyton.2023.028237

    Abstract Infection of plum bark necrosis stem pitting associated virus (PBNSPaV) has been reported in many Prunus species in several countries, causing significant economic losses. The very small proteins encoded by plant viruses are often overlooked due to their short sequences and uncertain significance. However, numerous studies have indicated that they might play important roles in the pathogenesis of virus infection. The role of small hydrophobic protein P6, encoded by the open reading frame 2 of PBNSPaV, has not been well explored. In this study, we amplified the P6 fragment from a PBNSPaV isolate by RT-PCR using specific primers and found… More >

  • Open Access

    ARTICLE

    A Progressive Approach to Generic Object Detection: A Two-Stage Framework for Image Recognition

    Muhammad Aamir1, Ziaur Rahman1,*, Waheed Ahmed Abro2, Uzair Aslam Bhatti3, Zaheer Ahmed Dayo1, Muhammad Ishfaq1

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6351-6373, 2023, DOI:10.32604/cmc.2023.038173

    Abstract Object detection in images has been identified as a critical area of research in computer vision image processing. Research has developed several novel methods for determining an object’s location and category from an image. However, there is still room for improvement in terms of detection efficiency. This study aims to develop a technique for detecting objects in images. To enhance overall detection performance, we considered object detection a two-fold problem, including localization and classification. The proposed method generates class-independent, high-quality, and precise proposals using an agglomerative clustering technique. We then combine these proposals with the relevant input image to train… More >

  • Open Access

    ARTICLE

    A Review and Analysis of Localization Techniques in Underwater Wireless Sensor Networks

    Seema Rani1, Anju1, Anupma Sangwan1, Krishna Kumar2, Kashif Nisar3, Tariq Rahim Soomro3, Ag. Asri Ag. Ibrahim4,*, Manoj Gupta5, Laxmi Chand5, Sadiq Ali Khan6

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5697-5715, 2023, DOI:10.32604/cmc.2023.033007

    Abstract In recent years, there has been a rapid growth in Underwater Wireless Sensor Networks (UWSNs). The focus of research in this area is now on solving the problems associated with large-scale UWSN. One of the major issues in such a network is the localization of underwater nodes. Localization is required for tracking objects and detecting the target. It is also considered tagging of data where sensed contents are not found of any use without localization. This is useless for application until the position of sensed content is confirmed. This article’s major goal is to review and analyze underwater node localization… More >

  • Open Access

    ARTICLE

    Analysis and Design of Surgical Instrument Localization Algorithm

    Siyu Lu1, Jun Yang1, Bo Yang1, Zhengtong Yin2, Mingzhe Liu3,*, Lirong Yin4, Wenfeng Zheng1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 669-685, 2023, DOI:10.32604/cmes.2023.027417

    Abstract With the help of surgical navigation system, doctors can operate on patients more intuitively and accurately. The positioning accuracy and real-time performance of surgical instruments are very important to the whole system. In this paper, we analyze and design the detection algorithm of surgical instrument location mark, and estimate the posture of surgical instrument. In addition, we optimized the pose by remapping. Finally, the algorithm of location mark detection proposed in this paper and the posture analysis data of surgical instruments are verified and analyzed through experiments. The final result shows a high accuracy. More >

  • Open Access

    ARTICLE

    Clustering Reference Images Based on Covisibility for Visual Localization

    Sangyun Lee1, Junekoo Kang2, Hyunki Hong2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2705-2725, 2023, DOI:10.32604/cmc.2023.034136

    Abstract In feature-based visual localization for small-scale scenes, local descriptors are used to estimate the camera pose of a query image. For large and ambiguous environments, learning-based hierarchical networks that employ local as well as global descriptors to reduce the search space of database images into a smaller set of reference views have been introduced. However, since global descriptors are generated using visual features, reference images with some of these features may be erroneously selected. In order to address this limitation, this paper proposes two clustering methods based on how often features appear as well as their covisibility. For both approaches,… More >

  • Open Access

    ARTICLE

    An Efficient Indoor Localization Based on Deep Attention Learning Model

    Amr Abozeid1,*, Ahmed I. Taloba1,2, Rasha M. Abd El-Aziz1,3, Alhanoof Faiz Alwaghid1, Mostafa Salem3, Ahmed Elhadad1,4

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2637-2650, 2023, DOI:10.32604/csse.2023.037761

    Abstract Indoor localization methods can help many sectors, such as healthcare centers, smart homes, museums, warehouses, and retail malls, improve their service areas. As a result, it is crucial to look for low-cost methods that can provide exact localization in indoor locations. In this context, image-based localization methods can play an important role in estimating both the position and the orientation of cameras regarding an object. Image-based localization faces many issues, such as image scale and rotation variance. Also, image-based localization’s accuracy and speed (latency) are two critical factors. This paper proposes an efficient 6-DoF deep-learning model for image-based localization. This… More >

  • Open Access

    ARTICLE

    Experimental Evaluation of Trilateration-Based Outdoor Localization with LoRaWAN

    Saeed Ahmed Magsi1,2,*, Mohd Haris Bin Md Khir1, Illani Bt Mohd Nawi1, Muath Al Hasan3, Zaka Ullah3, Fasih Ullah Khan4, Abdul Saboor5, Muhammad Aadil Siddiqui1,2

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 845-862, 2023, DOI:10.32604/cmc.2023.033636

    Abstract Long Range Wide Area Network (LoRaWAN) in the Internet of Things (IoT) domain has been the subject of interest for researchers. There is an increasing demand to localize these IoT devices using LoRaWAN due to the quickly growing number of IoT devices. LoRaWAN is well suited to support localization applications in IoTs due to its low power consumption and long range. Multiple approaches have been proposed to solve the localization problem using LoRaWAN. The Expected Signal Power (ESP) based trilateration algorithm has the significant potential for localization because ESP can identify the signal’s energy below the noise floor with no… More >

  • Open Access

    ARTICLE

    Visualization Techniques via MLBS for Personnel Management in Major Events

    Yu Su1,2,3, Lingjuan Hou2,3,*, Sinan Li1, Zhaochang Jiang1, Haoran Peng4

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 521-536, 2023, DOI:10.32604/csse.2022.028606

    Abstract Mobile location-based services (MLBS) refer to services around geographic location data. Mobile terminals use wireless communication networks (or satellite positioning systems) to obtain users’ geographic location coordinate information based on spatial databases and integrate with other information to provide users with required location-related services. The development of systems based on MLBS has significance and practical value. In this paper a visualization management information system for personnel in major events based on microservices, namely MEPMIS, is designed and implemented by using MLBS. The system consists of a server and a client app, and it has some functions including map search and… More >

  • Open Access

    ARTICLE

    Machine Learning Based Diagnosis for Diabetic Retinopathy for SKPD-PSC

    M. P. Thiruvenkatasuresh1,*, Surbhi Bhatia2, Shakila Basheer3, Pankaj Dadheech4

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1767-1782, 2023, DOI:10.32604/iasc.2023.033711

    Abstract The study aimed to apply to Machine Learning (ML) researchers working in image processing and biomedical analysis who play an extensive role in comprehending and performing on complex medical data, eventually improving patient care. Developing a novel ML algorithm specific to Diabetic Retinopathy (DR) is a challenge and need of the hour. Biomedical images include several challenges, including relevant feature selection, class variations, and robust classification. Although the current research in DR has yielded favourable results, several research issues need to be explored. There is a requirement to look at novel pre-processing methods to discard irrelevant features, balance the obtained… More >

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