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  • Open Access

    ARTICLE

    YOLO-RLC: An Advanced Target-Detection Algorithm for Surface Defects of Printed Circuit Boards Based on YOLOv5

    Yuanyuan Wang1,2,*, Jialong Huang1, Md Sharid Kayes Dipu1, Hu Zhao3, Shangbing Gao1,2, Haiyan Zhang1,2, Pinrong Lv1

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4973-4995, 2024, DOI:10.32604/cmc.2024.055839

    Abstract Printed circuit boards (PCBs) provide stable connections between electronic components. However, defective printed circuit boards may cause the entire equipment system to malfunction, resulting in incalculable losses. Therefore, it is crucial to detect defective printed circuit boards during the generation process. Traditional detection methods have low accuracy in detecting subtle defects in complex background environments. In order to improve the detection accuracy of surface defects on industrial printed circuit boards, this paper proposes a residual large kernel network based on YOLOv5 (You Only Look Once version 5) for PCBs surface defect detection, called YOLO-RLC (You… More >

  • Open Access

    ARTICLE

    Printed Circuit Board (PCB) Surface Micro Defect Detection Model Based on Residual Network with Novel Attention Mechanism

    Xinyu Hu, Defeng Kong*, Xiyang Liu, Junwei Zhang, Daode Zhang

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 915-933, 2024, DOI:10.32604/cmc.2023.046376

    Abstract Printed Circuit Board (PCB) surface tiny defect detection is a difficult task in the integrated circuit industry, especially since the detection of tiny defects on PCB boards with large-size complex circuits has become one of the bottlenecks. To improve the performance of PCB surface tiny defects detection, a PCB tiny defects detection model based on an improved attention residual network (YOLOX-AttResNet) is proposed. First, the unsupervised clustering performance of the K-means algorithm is exploited to optimize the channel weights for subsequent operations by feeding the feature mapping into the SENet (Squeeze and Excitation Network) attention… More >

  • Open Access

    ARTICLE

    Mobile-Deep Based PCB Image Segmentation Algorithm Research

    Lisang Liu1, Chengyang Ke1,*, He Lin2

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2443-2461, 2023, DOI:10.32604/cmc.2023.042582

    Abstract Aiming at the problems of inaccurate edge segmentation, the hole phenomenon of segmenting large-scale targets, and the slow segmentation speed of printed circuit boards (PCB) in the image segmentation process, a PCB image segmentation model Mobile-Deep based on DeepLabv3+ semantic segmentation framework is proposed. Firstly, the DeepLabv3+ feature extraction network is replaced by the lightweight model MobileNetv2, which effectively reduces the number of model parameters; secondly, for the problem of positive and negative sample imbalance, a new loss function is composed of Focal Loss combined with Dice Loss to solve the category imbalance and improve… More >

  • Open Access

    ARTICLE

    Inhibition of apoptosis-regulatory protein Siva-1 reverses multidrug resistance in gastric cancer by targeting PCBP1

    FANBIAO KONG1,2,#, KUN WU3,4,#, LIMING PANG2,#, YULIANG HUANG2,#, LEI LI3, JING XU2, FEITONG LI2, YAN QING2, ZHONGYU WANG2, XIURONG HUANG3, SHENG XU2, XIAOGANG ZHONG2, ZHOU ZHU2, XIAOTONG WANG3,*, JIANRONG YANG5,*

    Oncology Research, Vol.30, No.6, pp. 277-288, 2022, DOI:10.32604/or.2022.027301

    Abstract Introduction: Siva-1, as a pro-apoptotic protein, has been shown to induce extensive apoptosis in a number of different cell lines. In our previous study, we showed that overexpressed Siva-1 decreased the apoptosis of gastric cancer cells. So, we believe that it can also work as an anti-apoptotic protein. The present study aimed to determine the specific role of Siva-1 in anticancer drug resistance in gastric cancer in vivo and in vitro and preliminarily reveal the mechanism. Materials and Methods: A vincristine-resistant MKN-28/VCR gastric cancer cell line with stably downregulated Siva-1 was established. The effect of Siva-1 downregulation… More >

  • Open Access

    ARTICLE

    Algorithmic Scheme for Concurrent Detection and Classification of Printed Circuit Board Defects

    Jakkrit Onshaunjit, Jakkree Srinonchat*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 355-367, 2022, DOI:10.32604/cmc.2022.017698

    Abstract An ideal printed circuit board (PCB) defect inspection system can detect defects and classify PCB defect types. Existing defect inspection technologies can identify defects but fail to classify all PCB defect types. This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types. In the proposed algorithmic scheme, fuzzy c-means clustering is used for image segmentation via image subtraction prior to defect detection. Arithmetic and logic operations, the circle hough transform (CHT), morphological reconstruction (MR), and connected component labeling (CCL) are used in defect classification. The algorithmic scheme achieves More >

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