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  • Open Access

    ARTICLE

    Enhancing Early Detection of Lung Cancer through Advanced Image Processing Techniques and Deep Learning Architectures for CT Scans

    Nahed Tawfik1,*, Heba M. Emara2, Walid El-Shafai3, Naglaa F. Soliman4, Abeer D. Algarni4, Fathi E. Abd El-Samie4

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 271-307, 2024, DOI:10.32604/cmc.2024.052404 - 15 October 2024

    Abstract Lung cancer remains a major concern in modern oncology due to its high mortality rates and multifaceted origins, including hereditary factors and various clinical changes. It stands as the deadliest type of cancer and a significant cause of cancer-related deaths globally. Early diagnosis enables healthcare providers to administer appropriate treatment measures promptly and accurately, leading to improved prognosis and higher survival rates. The significant increase in both the incidence and mortality rates of lung cancer, particularly its ranking as the second most prevalent cancer among women worldwide, underscores the need for comprehensive research into efficient… More >

  • Open Access

    ARTICLE

    Automated Angle Detection for Industrial Production Lines Using Combined Image Processing Techniques

    Pawat Chunhachatrachai1,*, Chyi-Yeu Lin1,2

    Intelligent Automation & Soft Computing, Vol.39, No.4, pp. 599-618, 2024, DOI:10.32604/iasc.2024.055385 - 06 September 2024

    Abstract Angle detection is a crucial aspect of industrial automation, ensuring precise alignment and orientation of components in manufacturing processes. Despite the widespread application of computer vision in industrial settings, angle detection remains an underexplored domain, with limited integration into production lines. This paper addresses the need for automated angle detection in industrial environments by presenting a methodology that eliminates training time and higher computation cost on Graphics Processing Unit (GPU) from machine learning in computer vision (e.g., Convolutional Neural Networks (CNN)). Our approach leverages advanced image processing techniques and a strategic combination of algorithms, including More >

  • Open Access

    REVIEW

    A Systematic Review of Computer Vision Techniques for Quality Control in End-of-Line Visual Inspection of Antenna Parts

    Zia Ullah1,2,*, Lin Qi1, E. J. Solteiro Pires2, Arsénio Reis2, Ricardo Rodrigues Nunes2

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2387-2421, 2024, DOI:10.32604/cmc.2024.047572 - 15 August 2024

    Abstract The rapid evolution of wireless communication technologies has underscored the critical role of antennas in ensuring seamless connectivity. Antenna defects, ranging from manufacturing imperfections to environmental wear, pose significant challenges to the reliability and performance of communication systems. This review paper navigates the landscape of antenna defect detection, emphasizing the need for a nuanced understanding of various defect types and the associated challenges in visual detection. This review paper serves as a valuable resource for researchers, engineers, and practitioners engaged in the design and maintenance of communication systems. The insights presented here pave the way… More >

  • Open Access

    ARTICLE

    CAD of BCD from Thermal Mammogram Images Using Machine Learning

    D. Banumathy1,*, Osamah Ibrahim Khalaf2, Carlos Andrés Tavera Romero3, J. Indra4, Dilip Kumar Sharma5

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 667-685, 2022, DOI:10.32604/iasc.2022.025609 - 15 April 2022

    Abstract Lump in the breast, discharge of blood from the nipple, and deformation of the nipple/breast and its texture are the symptoms of breast cancer. Though breast cancer is very common in women, men can also get breast cancer. In the early stages, BCD makes use of Thermal Mammograms Breast Images (TMBI). The cost of treatment can be severely reduced in the early stages of detection. Based on the techniques of segmentation, the Breast Cancer Detection (BCD) works. Moreover, by providing a balanced, reliable and appropriate second opinion, a tremendous role has been played by ML… More >

  • Open Access

    ARTICLE

    Blood Group Classification System Based on Image Processing Techniques

    S. A. Shaban*, D. L. Elsheweikh

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 817-834, 2022, DOI:10.32604/iasc.2022.019500 - 22 September 2021

    Abstract The present paper proposes a novel system that automatically classifies the eight different blood groups according to the ABO and Rh blood group systems. The proposed system is developed by applying MATLAB’s image processing techniques on the blood sample images. These images are acquired from the laboratory using the slide test. It utilizes a mean filter for removing noise from blood sample images. In addition, the Contrast Limited Adaptive Histogram Equalization (CLAHE) is used for enhancing the image characteristics analysis. The proposed system also utilizes the automated threshold strategy (Otsu’s approach) for obtaining the blood… More >

  • Open Access

    ABSTRACT

    Measuring displacement of a bridge using multi-channel image processing techniques

    Jong-Jae Lee, Jong-Woong Park, Young-Soo Park, Hyung-Jo Jung

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.12, No.3, pp. 92-92, 2009, DOI:10.3970/icces.2009.012.092

    Abstract Measuring the displacement of a flexible bridge is difficult particularly on a long span bridge. In this study, real-time displacement measurement of a long span bridge was carried out using digital image processing techniques which require a target recognition algorithm, projection of the captured image, and calculation of the actual displacement using target geometry and the number of pixels moved. To measure the displacement of a bridge from a distant location which can be regarded as a fixed reference point, a novel image processing method has been devised. By measuring the same target with two More >

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