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  • Open Access

    ARTICLE

    Sign Language Recognition and Classification Model to Enhance Quality of Disabled People

    Fadwa Alrowais1, Saud S. Alotaibi2, Sami Dhahbi3,4, Radwa Marzouk5, Abdullah Mohamed6, Anwer Mustafa Hilal7,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3419-3432, 2022, DOI:10.32604/cmc.2022.029438 - 16 June 2022

    Abstract Sign language recognition can be considered as an effective solution for disabled people to communicate with others. It helps them in conveying the intended information using sign languages without any challenges. Recent advancements in computer vision and image processing techniques can be leveraged to detect and classify the signs used by disabled people in an effective manner. Metaheuristic optimization algorithms can be designed in a manner such that it fine tunes the hyper parameters, used in Deep Learning (DL) models as the latter considerably impacts the classification results. With this motivation, the current study designs… More >

  • Open Access

    ARTICLE

    Optimal Deep Transfer Learning Model for Histopathological Breast Cancer Classification

    Mahmoud Ragab1,2,3,*, Alaa F. Nahhas4

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2849-2864, 2022, DOI:10.32604/cmc.2022.028855 - 16 June 2022

    Abstract Earlier recognition of breast cancer is crucial to decrease the severity and optimize the survival rate. One of the commonly utilized imaging modalities for breast cancer is histopathological images. Since manual inspection of histopathological images is a challenging task, automated tools using deep learning (DL) and artificial intelligence (AI) approaches need to be designed. The latest advances of DL models help in accomplishing maximum image classification performance in several application areas. In this view, this study develops a Deep Transfer Learning with Rider Optimization Algorithm for Histopathological Classification of Breast Cancer (DTLRO-HCBC) technique. The proposed… More >

  • Open Access

    ARTICLE

    Development of Mobile App to Support the Mobility of Visually Impaired People

    R. Meenakshi1, R. Ponnusamy1,*, Saleh Alghamdi2, Osama Ibrahim Khalaf3, Youseef Alotaibi4

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3473-3495, 2022, DOI:10.32604/cmc.2022.028540 - 16 June 2022

    Abstract In 2017, it was estimated that the number of persons of all ages visually affected would be two hundred and eighty-five million, of which thirty-nine million are blind. There are several innovative technical solutions available to facilitate the movement of these people. The next big challenge for technical people is to give cost-effective solutions. One of the challenges for people with visual impairments is navigating safely, recognizing obstacles, and moving freely between locations in unfamiliar environments. A new mobile application solution is developed, and the application can be installed in android mobile. The application will More >

  • Open Access

    ARTICLE

    Multi-Scale Network with Integrated Attention Unit for Crowd Counting

    Adel Hafeezallah1, Ahlam Al-Dhamari2,3,*, Syed Abd Rahman Abu-Bakar2

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3879-3903, 2022, DOI:10.32604/cmc.2022.028289 - 16 June 2022

    Abstract Estimating the crowd count and density of highly dense scenes witnessed in Muslim gatherings at religious sites in Makkah and Madinah is critical for developing control strategies and organizing such a large gathering. Moreover, since the crowd images in this case can range from low density to high density, detection-based approaches are hard to apply for crowd counting. Recently, deep learning-based regression has become the prominent approach for crowd counting problems, where a density-map is estimated, and its integral is further computed to acquire the final count result. In this paper, we put forward a… More >

  • Open Access

    ARTICLE

    4D Facial Expression Recognition Using Geometric Landmark-based Axes-angle Feature Extraction

    Henry Ugochukwu Ukwu*, Kamil Yurtkan

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1819-1838, 2022, DOI:10.32604/iasc.2022.025695 - 25 May 2022

    Abstract The primary goal of this paper is to describe a proposed framework for identifying human face expressions. A methodology has been proposed and developed to identify facial emotions using an axes-angular feature extracted from facial landmarks for 4D dynamic facial expression video data. The 4D facial expression recognition (FER) problem is modeled as an unbalanced problem using the full video sequence. The proposed dataset includes landmarks that are positioned to be fiducial features: around the brows, eyes, nose, cheeks, and lips. Following the initial facial landmark preprocessing, feature extraction is carried out. Input feature vectors… More >

  • Open Access

    ARTICLE

    Computer Vision with Machine Learning Enabled Skin Lesion Classification Model

    Romany F. Mansour1,*, Sara A. Althubiti2, Fayadh Alenezi3

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 849-864, 2022, DOI:10.32604/cmc.2022.029265 - 18 May 2022

    Abstract Recently, computer vision (CV) based disease diagnosis models have been utilized in various areas of healthcare. At the same time, deep learning (DL) and machine learning (ML) models play a vital role in the healthcare sector for the effectual recognition of diseases using medical imaging tools. This study develops a novel computer vision with optimal machine learning enabled skin lesion detection and classification (CVOML-SLDC) model. The goal of the CVOML-SLDC model is to determine the appropriate class labels for the test dermoscopic images. Primarily, the CVOML-SLDC model derives a gaussian filtering (GF) approach to pre-process More >

  • Open Access

    ARTICLE

    Computer Vision Technology for Fault Detection Systems Using Image Processing

    Abed Saif Alghawli*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1961-1976, 2022, DOI:10.32604/cmc.2022.028990 - 18 May 2022

    Abstract In the period of Industries 4.0, cyber-physical systems (CPSs) were a major study area. Such systems frequently occur in manufacturing processes and people’s everyday lives, and they communicate intensely among physical elements and lead to inconsistency. Due to the magnitude and importance of the systems they support, the cyber quantum models must function effectively. In this paper, an image-processing-based anomalous mobility detecting approach is suggested that may be added to systems at any time. The expense of glitches, failures or destroyed products is decreased when anomalous activities are detected and unplanned scenarios are avoided. The… More >

  • Open Access

    ARTICLE

    Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

    Saman Riaz1, Ali Arshad2, Shahab S. Band3,*, Amir Mosavi4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4303-4321, 2022, DOI:10.32604/cmc.2022.024819 - 21 April 2022

    Abstract The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by… More >

  • Open Access

    ARTICLE

    Gender-specific Facial Age Group Classification Using Deep Learning

    Valliappan Raman1, Khaled ELKarazle2,*, Patrick Then2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 105-118, 2022, DOI:10.32604/iasc.2022.025608 - 15 April 2022

    Abstract Facial age is one of the prominent features needed to make decisions, such as accessing certain areas or resources, targeted advertising, or more straightforward decisions such as addressing one another. In machine learning, facial age estimation is a typical facial analysis subtask in which a model learns the different facial ageing features from several facial images. Despite several studies confirming a relationship between age and gender, very few studies explored the idea of introducing a gender-based system that consists of two separate models, each trained on a specific gender group. This study attempts to bridge… More >

  • Open Access

    ARTICLE

    A Fast Panoptic Segmentation Network for Self-Driving Scene Understanding

    Abdul Majid1, Sumaira Kausar1,*, Samabia Tehsin1, Amina Jameel2

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 27-43, 2022, DOI:10.32604/csse.2022.022590 - 23 March 2022

    Abstract In recent years, a gain in popularity and significance of science understanding has been observed due to the high paced progress in computer vision techniques and technologies. The primary focus of computer vision based scene understanding is to label each and every pixel in an image as the category of the object it belongs to. So it is required to combine segmentation and detection in a single framework. Recently many successful computer vision methods has been developed to aid scene understanding for a variety of real world application. Scene understanding systems typically involves detection and… More >

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