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  • Open Access

    ARTICLE

    Robust Human Interaction Recognition Using Extended Kalman Filter

    Tanvir Fatima Naik Bukht1, Abdulwahab Alazeb2, Naif Al Mudawi2, Bayan Alabdullah3, Khaled Alnowaiser4, Ahmad Jalal1, Hui Liu5,*

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2987-3002, 2024, DOI:10.32604/cmc.2024.053547 - 18 November 2024

    Abstract In the field of computer vision and pattern recognition, knowledge based on images of human activity has gained popularity as a research topic. Activity recognition is the process of determining human behavior based on an image. We implemented an Extended Kalman filter to create an activity recognition system here. The proposed method applies an HSI color transformation in its initial stages to improve the clarity of the frame of the image. To minimize noise, we use Gaussian filters. Extraction of silhouette using the statistical method. We use Binary Robust Invariant Scalable Keypoints (BRISK) and SIFT More >

  • Open Access

    PROCEEDINGS

    Ultrafast Self-Transport of Multi-Scale Droplets Driven by Laplace Pressure Difference and Capillary Suction

    Fujian Zhang1, Ziyang Wang1, Xiang Gao1, Zhongqiang Zhang1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011736

    Abstract Spontaneous droplet transport has broad application prospects in fields such as water collection and microfluidic chips. Despite extensive research in this area, droplet self-transport is still limited by issues such as slow transport velocity, short distance, and poor integrity. Here, a novel cross-hatch textured cone (CHTC) with multistage microchannels and circular grooves is proposed to realize ultrafast directional long-distance self-transport of multi-scale droplets. The CHTC triggers two modes of fluid transport: Droplet transport by Laplace pressure difference and capillary suction pressure-induced fluid transfer in microchannels on cone surfaces. By leveraging the coupling effect of the… More >

  • Open Access

    ARTICLE

    Pyramid Separable Channel Attention Network for Single Image Super-Resolution

    Congcong Ma1,3, Jiaqi Mi2, Wanlin Gao1,3, Sha Tao1,3,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4687-4701, 2024, DOI:10.32604/cmc.2024.055803 - 12 September 2024

    Abstract Single Image Super-Resolution (SISR) technology aims to reconstruct a clear, high-resolution image with more information from an input low-resolution image that is blurry and contains less information. This technology has significant research value and is widely used in fields such as medical imaging, satellite image processing, and security surveillance. Despite significant progress in existing research, challenges remain in reconstructing clear and complex texture details, with issues such as edge blurring and artifacts still present. The visual perception effect still needs further enhancement. Therefore, this study proposes a Pyramid Separable Channel Attention Network (PSCAN) for the… More >

  • Open Access

    ARTICLE

    Weber Law Based Approach for Multi-Class Image Forgery Detection

    Arslan Akram1,3, Javed Rashid2,3,4, Arfan Jaffar1, Fahima Hajjej5, Waseem Iqbal6, Nadeem Sarwar7,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 145-166, 2024, DOI:10.32604/cmc.2023.041074 - 30 January 2024

    Abstract Today’s forensic science introduces a new research area for digital image analysis for multimedia security. So, Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or create misleading publicity by using tempered images. Exiting forgery detection methods can classify only one of the most widely used Copy-Move and splicing forgeries. However, an image can contain one or more types of forgeries. This study has proposed a hybrid method for classifying Copy-Move and splicing images using texture information of images in the spatial domain. Firstly, More >

  • Open Access

    ARTICLE

    Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

    Shaik Mahaboob Basha1,*, Victor Hugo C. de Albuquerque2, Samia Allaoua Chelloug3,*, Mohamed Abd Elaziz4,5,6,7, Shaik Hashmitha Mohisin8, Suhail Parvaze Pathan9

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1981-2004, 2024, DOI:10.32604/cmes.2023.031425 - 17 November 2023

    Abstract Manual investigation of chest radiography (CXR) images by physicians is crucial for effective decision-making in COVID-19 diagnosis. However, the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning techniques. This study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies, including normal cases. Texture information is extracted using gray co-occurrence matrix (GLCM)-based features, while vessel-like features are obtained using Frangi, Sato, and Meijering filters. Machine learning models employing Decision Tree (DT) and Random Forest (RF) approaches are designed to categorize CXR images… More > Graphic Abstract

    Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

  • Open Access

    ARTICLE

    Recognizing Breast Cancer Using Edge-Weighted Texture Features of Histopathology Images

    Arslan Akram1,2, Javed Rashid2,3,4, Fahima Hajjej5, Sobia Yaqoob1,6, Muhammad Hamid7, Asma Irshad8, Nadeem Sarwar9,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1081-1101, 2023, DOI:10.32604/cmc.2023.041558 - 31 October 2023

    Abstract Around one in eight women will be diagnosed with breast cancer at some time. Improved patient outcomes necessitate both early detection and an accurate diagnosis. Histological images are routinely utilized in the process of diagnosing breast cancer. Methods proposed in recent research only focus on classifying breast cancer on specific magnification levels. No study has focused on using a combined dataset with multiple magnification levels to classify breast cancer. A strategy for detecting breast cancer is provided in the context of this investigation. Histopathology image texture data is used with the wavelet transform in this… More >

  • Open Access

    PROCEEDINGS

    Self-Driving Behavior and Pinning Effect of Droplets on GrapheneCovered Functional Textured Surfaces

    Fujian Zhang1, Xiang Gao1, Zhongqiang Zhang1,2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09169

    Abstract Biological features such as the bumps on the back of desert beetles and the spikes of cacti enable the directional transport of water droplets, creating conditions for their survival in nature. Inspired by the interesting natural phenomenon, a novel design of nanopillared surface with a gradient density of structural pillar matrix covered by a monolayer graphene is proposed to realize ultrafast self-driving of water droplets. The droplet can move spontaneously at ultrahigh speed of 75.7 m/s (272.52 km/h) from sparsest to densest regions of pillars while a wettability gradient is created by the gradient distribution… More >

  • Open Access

    PROCEEDINGS

    Shear Localization in Polycrystalline Metal at High-Strain Rates with Dynamic Recrystallization: Crystal Plasticity Modeling and Texture Effect

    Qilin Xiong1,2,*, Wen An1,2, Chuanzhi Liu1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010044

    Abstract Shear localization is an important failure mode, or even the dominant mode in metals at high-strain rates. However, it is a great challenge to accurately predict the occurrence and evolution of shear localization in metals at the high-strain rate deformation. Here, a dislocation-based crystal plasticity constitutive model with a crucial mechanism of shear instability, namely dynamic recrystallization, was developed. The evolution equations of dislocation density and grain size in the process of dynamic recrystallization were proposed and incorporated into the new constitutive model. The threshold of the stored energy in crystals was used as the… More >

  • Open Access

    ARTICLE

    Classification-Detection of Metal Surfaces under Lower Edge Sharpness Using a Deep Learning-Based Approach Combined with an Enhanced LoG Operator

    Hong Zhang1,*, Jiaming Zhou1, Qi Wang1, Chengxi Zhu1, Haijian Shao2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1551-1572, 2023, DOI:10.32604/cmes.2023.027035 - 26 June 2023

    Abstract Metal flat surface in-line surface defect detection is notoriously difficult due to obstacles such as high surface reflectivity, pseudo-defect interference, and random elastic deformation. This study evaluates the approach for detecting scratches on a metal surface in order to address a problem in the detection process. This paper proposes an improved Gauss-Laplace (LoG) operator combined with a deep learning technique for metal surface scratch identification in order to solve the difficulties that it is challenging to reduce noise and that the edges are unclear when utilizing existing edge detection algorithms. In the process of scratch… More >

  • Open Access

    ARTICLE

    Traffic Sign Detection with Low Complexity for Intelligent Vehicles Based on Hybrid Features

    Sara Khalid1, Jamal Hussain Shah1,*, Muhammad Sharif1, Muhammad Rafiq2, Gyu Sang Choi3,*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 861-879, 2023, DOI:10.32604/cmc.2023.035595 - 08 June 2023

    Abstract Globally traffic signs are used by all countries for healthier traffic flow and to protect drivers and pedestrians. Consequently, traffic signs have been of great importance for every civilized country, which makes researchers give more focus on the automatic detection of traffic signs. Detecting these traffic signs is challenging due to being in the dark, far away, partially occluded, and affected by the lighting or the presence of similar objects. An innovative traffic sign detection method for red and blue signs in color images is proposed to resolve these issues. This technique aimed to devise… More >

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