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  • Open Access

    ARTICLE

    LiDAR-Visual SLAM with Integrated Semantic and Texture Information for Enhanced Ecological Monitoring Vehicle Localization

    Yiqing Lu1, Liutao Zhao2,*, Qiankun Zhao3

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1401-1416, 2025, DOI:10.32604/cmc.2024.058757 - 03 January 2025

    Abstract Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors. These vehicles are crucial in various fields, including environmental science research, ecological and environmental monitoring projects, disaster response, and emergency management. A key method employed in these vehicles for achieving high-precision positioning is LiDAR (lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping (SLAM). However, maintaining high-precision localization in complex scenarios, such as degraded environments or when dynamic objects are present, remains a significant challenge. To address this issue, we integrate both semantic and… More >

  • Open Access

    ARTICLE

    Multi-Generator Discriminator Network Using Texture-Edge Information

    Kyeongseok Jang1, Seongsoo Cho2, Kwang Chul Son3,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3537-3551, 2023, DOI:10.32604/cmc.2023.030557 - 31 March 2023

    Abstract In the proposed paper, a parallel structure type Generative Adversarial Network (GAN) using edge and texture information is proposed. In the existing GAN-based model, many learning iterations had to be given to obtaining an output that was somewhat close to the original data, and noise and distortion occurred in the output image even when learning was performed. To solve this problem, the proposed model consists of two generators and three discriminators to propose a network in the form of a parallel structure. In the network, each edge information and texture information were received as inputs, More >

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