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  • Open Access


    Optimized Deep Learning Model for Fire Semantic Segmentation

    Songbin Li1,*, Peng Liu1, Qiandong Yan1, Ruiling Qian2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4999-5013, 2022, DOI:10.32604/cmc.2022.026498

    Abstract Recent convolutional neural networks (CNNs) based deep learning has significantly promoted fire detection. Existing fire detection methods can efficiently recognize and locate the fire. However, the accurate flame boundary and shape information is hard to obtain by them, which makes it difficult to conduct automated fire region analysis, prediction, and early warning. To this end, we propose a fire semantic segmentation method based on Global Position Guidance (GPG) and Multi-path explicit Edge information Interaction (MEI). Specifically, to solve the problem of local segmentation errors in low-level feature space, a top-down global position guidance module is More >

  • Open Access


    A Data-Aware Remote Procedure Call Method for Big Data Systems

    Jin Wang1,2, Yaqiong Yang1, Jingyu Zhang1,3,*, Xiaofeng Yu4, Osama Alfarraj5, Amr Tolba5,6

    Computer Systems Science and Engineering, Vol.35, No.6, pp. 523-532, 2020, DOI:10.32604/csse.2020.35.523

    Abstract In recent years, big data has been one of the hottest development directions in the information field. With the development of artificial intelligence technology, mobile smart terminals and high-bandwidth wireless Internet, various types of data are increasing exponentially. Huge amounts of data contain a lot of potential value, therefore how to effectively store and process data efficiently becomes very important. Hadoop Distributed File System (HDFS) has emerged as a typical representative of dataintensive distributed big data file systems, and it has features such as high fault tolerance, high throughput, and can be deployed on low-cost… More >

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