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  • Open Access

    ARTICLE

    A Novel Technique for Detecting Various Thyroid Diseases Using Deep Learning

    Soma Prathibha1,*, Deepak Dahiya2, C. R. Rene Robin3, Cherukuru Venkata Nishkala4, S. Swedha5

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 199-214, 2023, DOI:10.32604/iasc.2023.025819 - 06 June 2022

    Abstract Thyroid disease is a medical condition caused due to the excess release of thyroid hormone. It is released by the thyroid gland which is in front of the neck just below the larynx. Medical pictures such as X-rays and CT scans can, however, be used to diagnose it. In this proposed model, Deep Learning technology is used to detect thyroid diseases. A Convolution Neural Network (CNN) based modified ResNet architecture is employed to detect five different types of thyroid diseases namely 1. Hypothyroid 2. Hyperthyroid 3. Thyroid cancer 4. Thyroiditis 5. Thyroid nodules. In the… More >

  • Open Access

    ARTICLE

    Deep Neural Network Based Detection and Segmentation of Ships for Maritime Surveillance

    Kyamelia Roy1, Sheli Sinha Chaudhuri1, Sayan Pramanik2, Soumen Banerjee2,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 647-662, 2023, DOI:10.32604/csse.2023.024997 - 01 June 2022

    Abstract In recent years, computer vision finds wide applications in maritime surveillance with its sophisticated algorithms and advanced architecture. Automatic ship detection with computer vision techniques provide an efficient means to monitor as well as track ships in water bodies. Waterways being an important medium of transport require continuous monitoring for protection of national security. The remote sensing satellite images of ships in harbours and water bodies are the image data that aid the neural network models to localize ships and to facilitate early identification of possible threats at sea. This paper proposes a deep learning… More >

  • Open Access

    ARTICLE

    An Optimized and Hybrid Framework for Image Processing Based Network Intrusion Detection System

    Murtaza Ahmed Siddiqi, Wooguil Pak*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3921-3949, 2022, DOI:10.32604/cmc.2022.029541 - 16 June 2022

    Abstract The network infrastructure has evolved rapidly due to the ever-increasing volume of users and data. The massive number of online devices and users has forced the network to transform and facilitate the operational necessities of consumers. Among these necessities, network security is of prime significance. Network intrusion detection systems (NIDS) are among the most suitable approaches to detect anomalies and assaults on a network. However, keeping up with the network security requirements is quite challenging due to the constant mutation in attack patterns by the intruders. This paper presents an effective and prevalent framework for 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

    Pedestrian Physical Education Training Over Visualization Tool

    Tamara al Shloul1, Israr Akhter2, Suliman A. Alsuhibany3, Yazeed Yasin Ghadi4, Ahmad Jalal2, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2389-2405, 2022, DOI:10.32604/cmc.2022.027007 - 16 June 2022

    Abstract E-learning approaches are one of the most important learning platforms for the learner through electronic equipment. Such study techniques are useful for other groups of learners such as the crowd, pedestrian, sports, transports, communication, emergency services, management systems and education sectors. E-learning is still a challenging domain for researchers and developers to find new trends and advanced tools and methods. Many of them are currently working on this domain to fulfill the requirements of industry and the environment. In this paper, we proposed a method for pedestrian behavior mining of aerial data, using deep flow… More >

  • Open Access

    ARTICLE

    No-Reference Stereo Image Quality Assessment Based on Transfer Learning

    Lixiu Wu1,*, Song Wang2, Qingbing Sang3

    Journal of New Media, Vol.4, No.3, pp. 125-135, 2022, DOI:10.32604/jnm.2022.027199 - 13 June 2022

    Abstract In order to apply the deep learning to the stereo image quality evaluation, two problems need to be solved: The first one is that we have a bit of training samples, another is how to input the dimensional image’s left view or right view. In this paper, we transfer the 2D image quality evaluation model to the stereo image quality evaluation, and this method solves the first problem; use the method of principal component analysis is used to fuse the left and right views into an input image in order to solve the second problem. More >

  • Open Access

    ARTICLE

    An Enhanced Deep Learning Method for Skin Cancer Detection and Classification

    Mohamed W. Abo El-Soud1,2,*, Tarek Gaber2,3, Mohamed Tahoun2, Abdullah Alourani1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1109-1123, 2022, DOI:10.32604/cmc.2022.028561 - 18 May 2022

    Abstract The prevalence of melanoma skin cancer has increased in recent decades. The greatest risk from melanoma is its ability to broadly spread throughout the body by means of lymphatic vessels and veins. Thus, the early diagnosis of melanoma is a key factor in improving the prognosis of the disease. Deep learning makes it possible to design and develop intelligent systems that can be used in detecting and classifying skin lesions from visible-light images. Such systems can provide early and accurate diagnoses of melanoma and other types of skin diseases. This paper proposes a new method… More >

  • Open Access

    ARTICLE

    Lower-Limb Motion-Based Ankle-Foot Movement Classification Using 2D-CNN

    Narathip Chaobankoh1, Tallit Jumphoo1, Monthippa Uthansakul1, Khomdet Phapatanaburi2, Bura Sindthupakorn3, Supakit Rooppakhun4, Peerapong Uthansakul1,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1269-1282, 2022, DOI:10.32604/cmc.2022.027474 - 18 May 2022

    Abstract Recently, the Muscle-Computer Interface (MCI) has been extensively popular for employing Electromyography (EMG) signals to help the development of various assistive devices. However, few studies have focused on ankle foot movement classification considering EMG signals at limb position. This work proposes a new framework considering two EMG signals at a lower-limb position to classify the ankle movement characteristics based on normal walking cycles. For this purpose, we introduce a human ankle-foot movement classification method using a two-dimensional-convolutional neural network (2D-CNN) with low-cost EMG sensors based on lower-limb motion. The time-domain signals of EMG obtained from… More >

  • Open Access

    ARTICLE

    Voice to Face Recognition Using Spectral ERB-DMLP Algorithms

    Fauzi A. Bala1,2,*, Osman N. Ucan1, Oguz Bayat1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2187-2204, 2022, DOI:10.32604/cmc.2022.024205 - 18 May 2022

    Abstract Designing an authentication system for securing the power plants are important to allow only specific staffs of the power plant to access the certain blocks so that they can be restricted from using high risk-oriented equipment. This authentication is also vital to prevent any security threats or risks like compromises of business server, release of confidential data etc. Though conventional works attempted to accomplish better authentication, they lacked with respect to accuracy. Hence, the study aims to enhance the recognition rate by introducing a voice recognition system as a personal authentication based on Deep Learning… More >

  • Open Access

    ARTICLE

    Multiple Forgery Detection in Video Using Convolution Neural Network

    Vinay Kumar1,*, Vineet Kansal2, Manish Gaur2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1347-1364, 2022, DOI:10.32604/cmc.2022.023545 - 18 May 2022

    Abstract With the growth of digital media data manipulation in today’s era due to the availability of readily handy tampering software, the authenticity of records is at high risk, especially in video. There is a dire need to detect such problem and do the necessary actions. In this work, we propose an approach to detect the interframe video forgery utilizing the deep features obtained from the parallel deep neural network model and thorough analytical computations. The proposed approach only uses the deep features extracted from the CNN model and then applies the conventional mathematical approach to… More >

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