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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

    Detecting Deepfake Images Using Deep Learning Techniques and Explainable AI Methods

    Wahidul Hasan Abir1, Faria Rahman Khanam1, Kazi Nabiul Alam1, Myriam Hadjouni2, Hela Elmannai3, Sami Bourouis4, Rajesh Dey5, Mohammad Monirujjaman Khan1,*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2151-2169, 2023, DOI:10.32604/iasc.2023.029653

    Abstract Nowadays, deepfake is wreaking havoc on society. Deepfake content is created with the help of artificial intelligence and machine learning to replace one person’s likeness with another person in pictures or recorded videos. Although visual media manipulations are not new, the introduction of deepfakes has marked a breakthrough in creating fake media and information. These manipulated pictures and videos will undoubtedly have an enormous societal impact. Deepfake uses the latest technology like Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) to construct automated methods for creating fake content that is becoming increasingly difficult to detect with the human… More >

  • Open Access

    ERRATUM

    Procaine Inhibits the Proliferation and Migration of Colon Cancer Cells Through Inactivation of the ERK/MAPK/FAK Pathways by Regulation of RhoA

    Chang Li*, Shuohui Gao*, Xiaoping Li, Chang Li, Lianjun Ma§

    Oncology Research, Vol.28, No.6, pp. 675-679, 2020, DOI:10.3727/096504021X16137463165406

    Abstract Colon cancer is one of the most lethal varieties of cancer. Chemotherapy remains as one of the principal treatment approaches for colon cancer. The anticancer activity of procaine (PCA), which is a local anesthetic drug, has been explored in different studies. In our study, we aimed to explore the anticancer effect of PCA on colon cancer and its underlying mechanism. The results showed that PCA significantly inhibited cell viability, increased the percentage of apoptotic cells, and decreased the expression level of RhoA in HCT116 cells in a dose-dependent manner (p < 0.05 or p < 0.01). Moreover, PCA increased the… 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

    Cross-Modal Relation-Aware Networks for Fake News Detection

    Hui Yu, Jinguang Wang*

    Journal of New Media, Vol.4, No.1, pp. 13-26, 2022, DOI:10.32604/jnm.2022.027312

    Abstract With the speedy development of communication Internet and the widespread use of social multimedia, so many creators have published posts on social multimedia platforms that fake news detection has already been a challenging task. Although some works use deep learning methods to capture visual and textual information of posts, most existing methods cannot explicitly model the binary relations among image regions or text tokens to mine the global relation information in a modality deeply such as image or text. Moreover, they cannot fully exploit the supplementary cross-modal information, including image and text relations, to supplement and enrich each modality. In… More >

  • Open Access

    ARTICLE

    Fake News Classification Using a Fuzzy Convolutional Recurrent Neural Network

    Dheeraj Kumar Dixit*, Amit Bhagat, Dharmendra Dangi

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5733-5750, 2022, DOI:10.32604/cmc.2022.023628

    Abstract In recent years, social media platforms have gained immense popularity. As a result, there has been a tremendous increase in content on social media platforms. This content can be related to an individual's sentiments, thoughts, stories, advertisements, and news, among many other content types. With the recent increase in online content, the importance of identifying fake and real news has increased. Although, there is a lot of work present to detect fake news, a study on Fuzzy CRNN was not explored into this direction. In this work, a system is designed to classify fake and real news using fuzzy logic.… More >

  • Open Access

    ARTICLE

    Social Networks Fake Account and Fake News Identification with Reliable Deep Learning

    N. Kanagavalli1,*, S. Baghavathi Priya2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 191-205, 2022, DOI:10.32604/iasc.2022.022720

    Abstract Recent developments of the World Wide Web (WWW) and social networking (Twitter, Instagram, etc.) paves way for data sharing which has never been observed in the human history before. A major security issue in this network is the creation of fake accounts. In addition, the automatic classification of the text article as true or fake is also a crucial process. The ineffectiveness of humans in distinguishing the true and false information exposes the fake news as a risk to credibility, democracy, logical truth, and journalism in government sectors. Besides, the automatic fake news or rumors from the social networking sites… More >

  • Open Access

    ARTICLE

    Arabic Fake News Detection Using Deep Learning

    Khaled M. Fouad1,3, Sahar F. Sabbeh1,2,*, Walaa Medhat1,3

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3647-3665, 2022, DOI:10.32604/cmc.2022.021449

    Abstract Nowadays, an unprecedented number of users interact through social media platforms and generate a massive amount of content due to the explosion of online communication. However, because user-generated content is unregulated, it may contain offensive content such as fake news, insults, and harassment phrases. The identification of fake news and rumors and their dissemination on social media has become a critical requirement. They have adverse effects on users, businesses, enterprises, and even political regimes and governments. State of the art has tackled the English language for news and used feature-based algorithms. This paper proposes a model architecture to detect fake… More >

  • Open Access

    ARTICLE

    Detecting and Analysing Fake Opinions Using Artificial Intelligence Algorithms

    Mosleh Hmoud Al-Adhaileh1, Fawaz Waselallah Alsaade2,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 643-655, 2022, DOI:10.32604/iasc.2022.021225

    Abstract In e-commerce and on social media, identifying fake opinions has become a tremendous challenge. Such opinions are widely generated on the internet by fake viewers, also called fraudsters. They write deceptive reviews that purport to reflect actual user experience either to promote some products or to defame others. They also target the reputations of e-businesses. Their aim is to mislead customers to make a wrong purchase decision by selecting undesired products. Such reviewers are often paid by rival e-business companies to compose positive reviews of their products and/or negative reviews of other companies’ products. The main objective of this paper… More >

  • Open Access

    REVIEW

    Metformin and colorectal cancer

    GASTÓN AMABLE#, EDUARDO MARTÍNEZ-LEÓN#, MARÍA E. PICCO, OSVALDO REY

    BIOCELL, Vol.46, No.1, pp. 51-59, 2022, DOI:10.32604/biocell.2022.017565

    Abstract Colorectal cancer (CRC) is one of the main causes of cancer-related mortality in the developed world despite recent developments in detection and treatment. Several epidemiological studies indicate that metformin, a widely prescribed antidiabetic drug, exerts a protective effect on different cancers including CRC. Furthermore, a recent double-blind placebo-controlled, randomized trial showed that metformin significantly decreased colorectal adenoma recurrence. Studies exploring the mechanism of action of metformin in cells derived from different types of cancers reported many effects including respiratory chain complex 1 inhibition, Akt phosphorylation inhibition, ATP depletion, PKA activation and Wnt signaling inhibition. However, many of these results were… More >

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