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  • Open Access

    ARTICLE

    Real-Time Detection and Instance Segmentation of Strawberry in Unstructured Environment

    Chengjun Wang1,2, Fan Ding2,*, Yiwen Wang1, Renyuan Wu1, Xingyu Yao2, Chengjie Jiang1, Liuyi Ling1

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1481-1501, 2024, DOI:10.32604/cmc.2023.046876

    Abstract The real-time detection and instance segmentation of strawberries constitute fundamental components in the development of strawberry harvesting robots. Real-time identification of strawberries in an unstructured environment is a challenging task. Current instance segmentation algorithms for strawberries suffer from issues such as poor real-time performance and low accuracy. To this end, the present study proposes an Efficient YOLACT (E-YOLACT) algorithm for strawberry detection and segmentation based on the YOLACT framework. The key enhancements of the E-YOLACT encompass the development of a lightweight attention mechanism, pyramid squeeze shuffle attention (PSSA), for efficient feature extraction. Additionally, an attention-guided context-feature pyramid network (AC-FPN) is… More >

  • Open Access

    ARTICLE

    An Intelligent Detection Method for Optical Remote Sensing Images Based on Improved YOLOv7

    Chao Dong, Xiangkui Jiang*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3015-3036, 2023, DOI:10.32604/cmc.2023.044735

    Abstract To address the issue of imbalanced detection performance and detection speed in current mainstream object detection algorithms for optical remote sensing images, this paper proposes a multi-scale object detection model for remote sensing images on complex backgrounds, called DI-YOLO, based on You Only Look Once v7-tiny (YOLOv7-tiny). Firstly, to enhance the model’s ability to capture irregular-shaped objects and deformation features, as well as to extract high-level semantic information, deformable convolutions are used to replace standard convolutions in the original model. Secondly, a Content Coordination Attention Feature Pyramid Network (CCA-FPN) structure is designed to replace the Neck part of the original… More >

  • Open Access

    ARTICLE

    Towards Cache-Assisted Hierarchical Detection for Real-Time Health Data Monitoring in IoHT

    Muhammad Tahir1,2,*, Mingchu Li1,2, Irfan Khan1,2, Salman A. Al Qahtani3, Rubia Fatima4, Javed Ali Khan5, Muhammad Shahid Anwar6

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2529-2544, 2023, DOI:10.32604/cmc.2023.042403

    Abstract Real-time health data monitoring is pivotal for bolstering road services’ safety, intelligence, and efficiency within the Internet of Health Things (IoHT) framework. Yet, delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems. We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this. This strategy is devised to streamline the data retrieval path, subsequently diminishing network strain. Crafting an adept cache processing scheme poses its own set of challenges, especially given the transient nature of monitoring data and the imperative for swift data transmission, intertwined with resource allocation tactics.… More >

  • Open Access

    ARTICLE

    Quick and Accurate Counting of Rapeseed Seedling with Improved YOLOv5s and Deep-Sort Method

    Chen Su, Jie Hong, Jiang Wang, Yang Yang*

    Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2611-2632, 2023, DOI:10.32604/phyton.2023.029457

    Abstract The statistics of the number of rapeseed seedlings are very important for breeders and planters to conduct seed quality testing, field crop management and yield estimation. Calculating the number of seedlings is inefficient and cumbersome in the traditional method. In this study, a method was proposed for efficient detection and calculation of rapeseed seedling number based on improved you only look once version 5 (YOLOv5) to identify objects and deep-sort to perform object tracking for rapeseed seedling video. Coordinated attention (CA) mechanism was added to the trunk of the improved YOLOv5s, which made the model more effective in identifying shaded,… More >

  • Open Access

    ARTICLE

    Real-Time Multi-Class Infection Classification for Respiratory Diseases

    Ahmed ElShafee1, Walid El-Shafai2, Abdulaziz Alarifi3,*, Mohammed Amoon3, Aman Singh4, Moustafa H. Aly5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4157-4177, 2022, DOI:10.32604/cmc.2022.028847

    Abstract Real-time disease prediction has emerged as the main focus of study in the field of computerized medicine. Intelligent disease identification framework can assist medical practitioners in diagnosing disease in a way that is reliable, consistent, and timely, successfully lowering mortality rates, particularly during endemics and pandemics. To prevent this pandemic’s rapid and widespread, it is vital to quickly identify, confine, and treat affected individuals. The need for auxiliary computer-aided diagnostic (CAD) systems has grown. Numerous recent studies have indicated that radiological pictures contained critical information regarding the COVID-19 virus. Utilizing advanced convolutional neural network (CNN) architectures in conjunction with radiological… More >

  • Open Access

    ARTICLE

    IoT Services: Realizing Private Real-Time Detection via Authenticated Conjunctive Searchable Encryption

    Chungen Xu1,*, Lin Mei1, Jinxue Cheng2, Yu Zhao1, Cong Zuo3

    Journal of Cyber Security, Vol.3, No.1, pp. 55-67, 2021, DOI:10.32604/jcs.2021.017217

    Abstract With the rapid development of wireless communication technology, the Internet of Things is playing an increasingly important role in our everyday. The amount of data generated by sensor devices is increasing as a large number of connectable devices are deployed in many fields, including the medical, agricultural, and industrial areas. Uploading data to the cloud solves the problem of data overhead but results in privacy issues. Therefore, the question of how to manage the privacy of uploading data and make it available to be interconnected between devices is a crucial issue. In this paper, we propose a scheme that supports… More >

  • Open Access

    ARTICLE

    Online Magnetic Flux Leakage Detection System for Sucker Rod Defects Based on LabVIEW Programming

    Ou Zhang1,*, Xueye Wei1

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 529-544, 2019, DOI:10.32604/cmc.2019.04075

    Abstract Aiming at the detection of the sucker rod defects, a real-time detection system is designed using the non-destructive testing technology of magnetic flux leakage (MFL). An MFL measurement system consists of many parts, and this study focuses on the signal acquisition and processing system. First of all, this paper introduces the hardware part of the acquisition system in detail, including the selection of the Hall-effect sensor, the design of the signal conditioning circuit, and the working process of the single chip computer (SCM) control serial port. Based on LabVIEW, a graphical programming software, the software part of the acquisition system… More >

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