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  • Open Access

    ARTICLE

    Deep Fake Detection Using Computer Vision-Based Deep Neural Network with Pairwise Learning

    R. Saravana Ram1, M. Vinoth Kumar2, Tareq M. Al-shami3, Mehedi Masud4, Hanan Aljuaid5, Mohamed Abouhawwash6,7,*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2449-2462, 2023, DOI:10.32604/iasc.2023.030486

    Abstract Deep learning-based approaches are applied successfully in many fields such as deepFake identification, big data analysis, voice recognition, and image recognition. Deepfake is the combination of deep learning in fake creation, which states creating a fake image or video with the help of artificial intelligence for political abuse, spreading false information, and pornography. The artificial intelligence technique has a wide demand, increasing the problems related to privacy, security, and ethics. This paper has analyzed the features related to the computer vision of digital content to determine its integrity. This method has checked the computer vision features of the image frames… More >

  • Open Access

    ARTICLE

    Natural Language Processing with Optimal Deep Learning Based Fake News Classification

    Sara A. Althubiti1, Fayadh Alenezi2, Romany F. Mansour3,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3529-3544, 2022, DOI:10.32604/cmc.2022.028981

    Abstract The recent advancements made in World Wide Web and social networking have eased the spread of fake news among people at a faster rate. At most of the times, the intention of fake news is to misinform the people and make manipulated societal insights. The spread of low-quality news in social networking sites has a negative influence upon people as well as the society. In order to overcome the ever-increasing dissemination of fake news, automated detection models are developed using Artificial Intelligence (AI) and Machine Learning (ML) methods. The latest advancements in Deep Learning (DL) models and complex Natural Language… More >

  • Open Access

    ARTICLE

    Intelligent Deep Learning Enabled Human Activity Recognition for Improved Medical Services

    E. Dhiravidachelvi1, M.Suresh Kumar2, L. D. Vijay Anand3, D. Pritima4, Seifedine Kadry5, Byeong-Gwon Kang6, Yunyoung Nam7,*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 961-977, 2023, DOI:10.32604/csse.2023.024612

    Abstract Human Activity Recognition (HAR) has been made simple in recent years, thanks to recent advancements made in Artificial Intelligence (AI) techniques. These techniques are applied in several areas like security, surveillance, healthcare, human-robot interaction, and entertainment. Since wearable sensor-based HAR system includes in-built sensors, human activities can be categorized based on sensor values. Further, it can also be employed in other applications such as gait diagnosis, observation of children/adult’s cognitive nature, stroke-patient hospital direction, Epilepsy and Parkinson’s disease examination, etc. Recently-developed Artificial Intelligence (AI) techniques, especially Deep Learning (DL) models can be deployed to accomplish effective outcomes on HAR process.… More >

  • Open Access

    ARTICLE

    Optimized Deep Learning Methods for Crop Yield Prediction

    K. Vignesh1,*, A. Askarunisa2, A. M. Abirami3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1051-1067, 2023, DOI:10.32604/csse.2023.024475

    Abstract Crop yield has been predicted using environmental, land, water, and crop characteristics in a prospective research design. When it comes to predicting crop production, there are a number of factors to consider, including weather conditions, soil qualities, water levels and the location of the farm. A broad variety of algorithms based on deep learning are used to extract useful crops for forecasting. The combination of data mining and deep learning creates a whole crop yield prediction system that is able to connect raw data to predicted crop yields. The suggested study uses a Discrete Deep belief network with Visual Geometry… More >

  • Open Access

    ARTICLE

    Deep Learning Based Autonomous Transport System for Secure Vehicle and Cargo Matching

    T. Shanthi1,*, M. Ramprasath2, A. Kavitha3, T. Muruganantham4

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 957-969, 2023, DOI:10.32604/iasc.2023.027775

    Abstract The latest 6G improvements secured autonomous driving's realism in Intelligent Autonomous Transport Systems (IATS). Despite the IATS's benefits, security remains a significant challenge. Blockchain technology has grown in popularity as a means of implementing safe, dependable, and decentralised independent IATS systems, allowing for more utilisation of legacy IATS infrastructures and resources, which is especially advantageous for crowdsourcing technologies. Blockchain technology can be used to address security concerns in the IATS and to aid in logistics development. In light of the inadequacy of reliance and inattention to rights created by centralised and conventional logistics systems, this paper discusses the creation of… More >

  • Open Access

    ARTICLE

    Multi-View Auxiliary Diagnosis Algorithm for Lung Nodules

    Shi Qiu1, Bin Li2,*, Tao Zhou3, Feng Li4, Ting Liang5

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4897-4910, 2022, DOI:10.32604/cmc.2022.026855

    Abstract Lung is an important organ of human body. More and more people are suffering from lung diseases due to air pollution. These diseases are usually highly infectious. Such as lung tuberculosis, novel coronavirus COVID-19, etc. Lung nodule is a kind of high-density globular lesion in the lung. Physicians need to spend a lot of time and energy to observe the computed tomography image sequences to make a diagnosis, which is inefficient. For this reason, the use of computer-assisted diagnosis of lung nodules has become the current main trend. In the process of computer-aided diagnosis, how to reduce the false positive… More >

  • Open Access

    ARTICLE

    An Efficient Video Inpainting Approach Using Deep Belief Network

    M. Nuthal Srinivasan1,*, M. Chinnadurai2

    Computer Systems Science and Engineering, Vol.43, No.2, pp. 515-529, 2022, DOI:10.32604/csse.2022.023109

    Abstract The video inpainting process helps in several video editing and restoration processes like unwanted object removal, scratch or damage rebuilding, and retargeting. It intends to fill spatio-temporal holes with reasonable content in the video. Inspite of the recent advancements of deep learning for image inpainting, it is challenging to outspread the techniques into the videos owing to the extra time dimensions. In this view, this paper presents an efficient video inpainting approach using beetle antenna search with deep belief network (VIA-BASDBN). The proposed VIA-BASDBN technique initially converts the videos into a set of frames and they are again split into… More >

  • Open Access

    ARTICLE

    An Optimal Deep Learning for Cooperative Intelligent Transportation System

    K. Lakshmi1, Srinivas Nagineni2, E. Laxmi Lydia3, A. Francis Saviour Devaraj4, Sachi Nandan Mohanty5, Irina V. Pustokhina6,*, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 19-35, 2022, DOI:10.32604/cmc.2022.020244

    Abstract Cooperative Intelligent Transport System (C-ITS) plays a vital role in the future road traffic management system. A vital element of C-ITS comprises vehicles, road side units, and traffic command centers, which produce a massive quantity of data comprising both mobility and service-related data. For the extraction of meaningful and related details out of the generated data, data science acts as an essential part of the upcoming C-ITS applications. At the same time, prediction of short-term traffic flow is highly essential to manage the traffic accurately. Due to the rapid increase in the amount of traffic data, deep learning (DL) models… More >

  • Open Access

    ARTICLE

    Virtual Nursing Using Deep Belief Networks for Elderly People (DBN-EP)

    S. Rajasekaran1,*, G. Kousalya2

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 985-1000, 2022, DOI:10.32604/csse.2022.022234

    Abstract The demand for better health services has resulted in the advancement of remote monitoring health, i.e., virtual nursing systems, to watch and support the elderly with innovative concepts such as being patient-centric, easier to use, and having smarter interactions and more accurate conclusions. While virtual nursing services attempt to provide consumers and medical practitioners with continuous medical and health monitoring services, access to allied healthcare experts such as nurses remains a challenge. In this research, we present Virtual Nursing Using Deep Belief Networks for Elderly People (DBN-EP), a new framework that provides a virtual nurse agent deployed on a senior… More >

  • Open Access

    ARTICLE

    Face Recognition System Using Deep Belief Network and Particle Swarm Optimization

    K. Babu1,*, C. Kumar2, C. Kannaiyaraju3

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 317-329, 2022, DOI:10.32604/iasc.2022.023756

    Abstract Facial expression for different emotional feelings makes it interesting for researchers to develop recognition techniques. Facial expression is the outcome of emotions they feel, behavioral acts, and the physiological condition of one’s mind. In the world of computer visions and algorithms, precise facial recognition is tough. In predicting the expression of a face, machine learning/artificial intelligence plays a significant role. The deep learning techniques are widely used in more challenging real-world problems which are highly encouraged in facial emotional analysis. In this article, we use three phases for facial expression recognition techniques. The principal component analysis-based dimensionality reduction techniques are… More >

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