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  • Open Access

    ARTICLE

    Real-time Safety Helmet-wearing Detection Based on Improved YOLOv5

    Yanman Li1, Jun Zhang1, Yang Hu1, Yingnan Zhao2,*, Yi Cao3

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1219-1230, 2022, DOI:10.32604/csse.2022.028224 - 09 May 2022

    Abstract Safety helmet-wearing detection is an essential part of the intelligent monitoring system. To improve the speed and accuracy of detection, especially small targets and occluded objects, it presents a novel and efficient detector model. The underlying core algorithm of this model adopts the YOLOv5 (You Only Look Once version 5) network with the best comprehensive detection performance. It is improved by adding an attention mechanism, a CIoU (Complete Intersection Over Union) Loss function, and the Mish activation function. First, it applies the attention mechanism in the feature extraction. The network can learn the weight of… More >

  • Open Access

    ARTICLE

    Design Features of Grocery Product Recognition Using Deep Learning

    E. Gothai1,*, Surbhi Bhatia2, Aliaa M. Alabdali3, Dilip Kumar Sharma4, Bhavana Raj Kondamudi5, Pankaj Dadheech6

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1231-1246, 2022, DOI:10.32604/iasc.2022.026264 - 03 May 2022

    Abstract At a grocery store, product supply management is critical to its employee's ability to operate productively. To find the right time for updating the item in terms of design/replenishment, real-time data on item availability are required. As a result, the item is consistently accessible on the rack when the client requires it. This study focuses on product display management at a grocery store to determine a particular product and its quantity on the shelves. Deep Learning (DL) is used to determine and identify every item and the store's supervisor compares all identified items with a… More >

  • Open Access

    ARTICLE

    Data Traffic Reduction with Compressed Sensing in an AIoT System

    Hye-Min Kwon1, Seng-Phil Hong2, Mingoo Kang1, Jeongwook Seo1,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1769-1780, 2022, DOI:10.32604/cmc.2022.020027 - 07 September 2021

    Abstract To provide Artificial Intelligence (AI) services such as object detection, Internet of Things (IoT) sensor devices should be able to send a large amount of data such as images and videos. However, this inevitably causes IoT networks to be severely overloaded. In this paper, therefore, we propose a novel oneM2M-compliant Artificial Intelligence of Things (AIoT) system for reducing overall data traffic and offering object detection. It consists of some IoT sensor devices with random sampling functions controlled by a compressed sensing (CS) rate, an IoT edge gateway with CS recovery and domain transform functions related… More >

  • Open Access

    ARTICLE

    Research of Insect Recognition Based on Improved YOLOv5

    Zhong Yuan1, Wei Fang1,2,*, Yongming Zhao3,*, Victor S. Sheng4

    Journal on Artificial Intelligence, Vol.3, No.4, pp. 145-152, 2021, DOI:10.32604/jai.2021.026902 - 07 February 2022

    Abstract Insects play an important role in the natural ecology, it is of great significance for ecology to research on insects. Nowadays, the invasion of alien species has brought serious troubles and a lot of losses to local life. However, there is still much room for improvement in the accuracy of insect recognition to effectively prevent the invasion of alien species. As the latest target detection algorithm, YOLOv5 has been used in various scene detection tasks, because of its powerful recognition capabilities and extremely high accuracy. As the problem of imbalance of feature maps at different… More >

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