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  • Open Access

    ARTICLE

    TCR-RoadNet: A Transformer-Enhanced Multi-Task Deep Learning Architecture for Real-Time Road Damage Detection and Segmentation

    Olzhas Olzhayev1, Bakhytzhan Kulambayev2,*, Azizah Suliman3

    CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.082618 - 23 July 2026

    Abstract Automated road damage detection is a critical component of intelligent transportation systems, enabling efficient infrastructure maintenance and improved traffic safety. However, existing approaches often suffer from limited contextual understanding, insufficient segmentation accuracy, and suboptimal real-time performance. This study presents TCR-RoadNet, a transformer-enhanced multi-task deep learning architecture designed for simultaneous road damage detection and segmentation in real-world driving environments. The proposed framework integrates a multi-scale convolutional backbone with a Transformer Context Refinement (TCR) module to capture both fine-grained structural details and long-range spatial dependencies across feature scales. To further enhance performance, a Decoupled Detection Head (DDH)… More >

  • Open Access

    ARTICLE

    A Lightweight Multiscale Feature Fusion Network for Solar Cell Defect Detection

    Xiaoyun Chen1, Lanyao Zhang1, Xiaoling Chen1, Yigang Cen2, Linna Zhang1,*, Fugui Zhang1

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 521-542, 2025, DOI:10.32604/cmc.2024.058063 - 03 January 2025

    Abstract Solar cell defect detection is crucial for quality inspection in photovoltaic power generation modules. In the production process, defect samples occur infrequently and exhibit random shapes and sizes, which makes it challenging to collect defective samples. Additionally, the complex surface background of polysilicon cell wafers complicates the accurate identification and localization of defective regions. This paper proposes a novel Lightweight Multi-scale Feature Fusion network (LMFF) to address these challenges. The network comprises a feature extraction network, a multi-scale feature fusion module (MFF), and a segmentation network. Specifically, a feature extraction network is proposed to obtain… More >

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