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  • Open Access

    ARTICLE

    Photovoltaic Cell Panels Soiling Inspection Using Principal Component Thermal Image Processing

    A. Sriram1,*, T. D. Sudhakar2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2761-2772, 2023, DOI:10.32604/csse.2023.028559 - 21 December 2022

    Abstract Intended for good productivity and perfect operation of the solar power grid a failure-free system is required. Therefore, thermal image processing with the thermal camera is the latest non-invasive (without manual contact) type fault identification technique which may give good precision in all aspects. The soiling issue, which is major productivity affecting factor may import from several reasons such as dust on the wind, bird mucks, etc. The efficient power production sufferers due to accumulated soil deposits reaching from 1%–7% in the county, such as India, to more than 25% in middle-east countries country, such… More >

  • Open Access

    ARTICLE

    Low-Cost Real-Time Automated Optical Inspection Using Deep Learning and Attention Map

    Yu Shih, Chien-Chih Kuo, Ching-Hung Lee*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2087-2099, 2023, DOI:10.32604/iasc.2023.027659 - 19 July 2022

    Abstract The recent trends in Industry 4.0 and Internet of Things have encouraged many factory managers to improve inspection processes to achieve automation and high detection rates. However, the corresponding cost results of sample tests are still used for quality control. A low-cost automated optical inspection system that can be integrated with production lines to fully inspect products without adjustments is introduced herein. The corresponding mechanism design enables each product to maintain a fixed position and orientation during inspection to accelerate the inspection process. The proposed system combines image recognition and deep learning to measure the More >

  • Open Access

    ARTICLE

    Build Gaussian Distribution Under Deep Features for Anomaly Detection and Localization

    Mei Wang1,*, Hao Xu2, Yadang Chen1

    Journal of New Media, Vol.4, No.4, pp. 179-190, 2022, DOI:10.32604/jnm.2022.032447 - 12 December 2022

    Abstract Anomaly detection in images has attracted a lot of attention in the field of computer vision. It aims at identifying images that deviate from the norm and segmenting the defect within images. However, anomalous samples are difficult to collect comprehensively, and labeled data is costly to obtain in many practical scenarios. We proposes a simple framework for unsupervised anomaly detection. Specifically, the proposed method directly employs CNN pre-trained on ImageNet to extract deep features from normal images and reduce dimensionality based on Principal Components Analysis (PCA), then build the distribution of normal features via the More >

  • Open Access

    ARTICLE

    Multi-Classification and Distributed Reinforcement Learning-Based Inspection Swarm Offloading Strategy

    Yuping Deng1, Tao Wu1, Xi Chen2,*, Amir Homayoon Ashrafzadeh3

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1157-1174, 2022, DOI:10.32604/iasc.2022.022606 - 03 May 2022

    Abstract In meteorological and electric power Internet of Things scenarios, in order to extend the service life of relevant facilities and reduce the cost of emergency repair, the intelligent inspection swarm is introduced to cooperate with monitoring tasks, which collect and process the current scene data through a variety of sensors and cameras, and complete tasks such as emergency handling and fault inspection. Due to the limitation of computing resources and battery life of patrol inspection equipment, it will cause problems such as slow response in emergency and long time for fault location. Mobile Edge Computing… 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 - 03 November 2021

    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 >

  • Open Access

    ARTICLE

    A Smart Deep Convolutional Neural Network for Real-Time Surface Inspection

    Adriano G. Passos, Tiago Cousseau, Marco A. Luersen*

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 583-593, 2022, DOI:10.32604/csse.2022.020020 - 25 October 2021

    Abstract A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of More >

  • Open Access

    ARTICLE

    Methodology for Road Defect Detection and Administration Based on Mobile Mapping Data

    Marina Davidović1,*, Tatjana Kuzmić1, Dejan Vasić1, Valentin Wich2, Ansgar Brunn2, Vladimir Bulatović1

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 207-226, 2021, DOI:10.32604/cmes.2021.016071 - 24 August 2021

    Abstract A detailed inspection of roads requires highly detailed spatial data with sufficient precision to deliver an accurate geometry and to describe road defects visually. This paper presents a novel method for the detection of road defects. The input data for road defect detection included point clouds and orthomosaics gathered by mobile mapping technology. The defects were categorized in three major groups with the following geometric primitives: points, lines and polygons. The method suggests the detection of point objects from matched point clouds, panoramic images and ortho photos. Defects were mapped as point, line or polygon… More >

  • Open Access

    ARTICLE

    Improved Attribute Chain Sampling Plan for Darna Distribution

    Harsh Tripathi1, Amer Ibrahim Al-Omari2, Mahendra Saha1, Ayed R. A. Alanzi3,*

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 381-392, 2021, DOI:10.32604/csse.2021.015624 - 19 May 2021

    Abstract Recently, the Darna distribution has been introduced as a new lifetime distribution. The two-parameter Darna distribution represents is a mixture of two well-known gamma and exponential distributions. A manufacturer or an engineer of products conducts life testing to examine whether the quality level of products meets the customer’s requirements, such as reliability or the minimum lifetime. In this article, an attribute modified chain sampling inspection plan based on the time truncated life test is proposed for items whose lifetime follows the Darna distribution. The plan parameters, including the sample size, the acceptance number, and the… More >

  • Open Access

    ARTICLE

    Tyre Inspection through Multi-State Convolutional Neural Networks

    C. Sivamani1, M. Rajeswari2, E. Golden Julie3, Y. Harold Robinson4, Vimal Shanmuganathan5, Seifedine Kadry6, Yunyoung Nam7,*

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 1-13, 2021, DOI:10.32604/iasc.2021.013705 - 07 January 2021

    Abstract Road accident is a potential risk to the lives of both drivers and passers-by. Many road accidents occur due to the improper condition of the vehicle tyres after long term usage. Thus, tyres need to be inspected and analyzed while manufacturing to avoid serious road problems. However, tyre wear is a multifaceted happening. It normally needs the non-linearly on many limitations, like tyre formation and plan, vehicle category, conditions of the road. Yet, tyre wear has numerous profitable and environmental inferences particularly due to maintenance costs and traffic safety implications. Thus, the risk to calculate… More >

  • Open Access

    ARTICLE

    Edge-Computing with Graph Computation: A Novel Mechanism to Handle Network Intrusion and Address Spoofing in SDN

    Rashid Amin1, *, Mudassar Hussain2, Mohammed Alhameed3, Syed Mohsan Raza4, Fathe Jeribi3, Ali Tahir3

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1869-1890, 2020, DOI:10.32604/cmc.2020.011758 - 16 September 2020

    Abstract Software Defined Networking (SDN) being an emerging network control model is widely recognized as a control and management platform. This model provides efficient techniques to control and manage the enterprise network. Another emerging paradigm is edge computing in which data processing is performed at the edges of the network instead of a central controller. This data processing at the edge nodes reduces the latency and bandwidth requirements. In SDN, the controller is a single point of failure. Several security issues related to the traditional network can be solved by using SDN central management and control.… More >

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