Tamara al Shloul¹, Israr Akhter², Suliman A. Alsuhibany³, Yazeed Yasin Ghadi⁴, Ahmad Jalal², Jeongmin Park^5,*

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

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 feature, graph mining technique, and… More >

Lixiu Wu^1,*, Song Wang², Qingbing Sang³

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

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. At the same time, the… More >

Soma Prathibha^1,*, 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

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 proposed work, the training method… More >

Kyamelia Roy¹, Sheli Sinha Chaudhuri¹, Sayan Pramanik², Soumen Banerjee^2,*

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

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 based model capable enough to… More >

Mohamed W. Abo El-Soud^1,2,*, Tarek Gaber^2,3, Mohamed Tahoun², Abdullah Alourani¹

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

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 which can be used for… More >

Narathip Chaobankoh¹, Tallit Jumphoo¹, Monthippa Uthansakul¹, Khomdet Phapatanaburi², Bura Sindthupakorn³, Supakit Rooppakhun⁴, Peerapong Uthansakul^1,*

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

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 two sensors belonging to Dorsiflexion,… More >

Fauzi A. Bala^1,2,*, Osman N. Ucan¹, Oguz Bayat¹

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

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 (DL) due to its ability… More >

Vinay Kumar^1,*, Vineet Kansal², Manish Gaur²

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

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 these features to find the… More >

A. Geetha, N. B. Prakash^*

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1041-1055, 2022, DOI:10.32604/csse.2022.023680

Abstract Today, many eye diseases jeopardize our everyday lives, such as Diabetic Retinopathy (DR), Age-related Macular Degeneration (AMD), and Glaucoma. Glaucoma is an incurable and unavoidable eye disease that damages the vision of optic nerves and quality of life. Classification of Glaucoma has been an active field of research for the past ten years. Several approaches for Glaucoma classification are established, beginning with conventional segmentation methods and feature-extraction to deep-learning techniques such as Convolution Neural Networks (CNN). In contrast, CNN classifies the input images directly using tuned parameters of convolution and pooling layers by extracting features. But, the volume of training… More >

Dokyung Hwang¹, Hyeonmin Ro¹, Naejoung Kwak², Jinsang Hwang³, Dongju Kim^1,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4411-4431, 2022, DOI:10.32604/cmc.2022.025378

Abstract A novel practical and universal method of mask-wearing detection has been proposed to prevent viral respiratory infections. The proposed method quickly and accurately detects mask and facial regions using well-trained You Only Look Once (YOLO) detector, then applies image coordinates of the detected bounding box (bbox). First, the data that is used to train our model is collected under various circumstances such as light disturbances, distances, time variations, and different climate conditions. It also contains various mask types to detect in general and universal application of the model. To detect mask-wearing status, it is important to detect facial and mask… More >