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21 articles for “Generative Learning”
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Research ArticleOpen accessEvery word in the titleA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,695 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid Pipelines for Intelligent Human Resources Text Classification: LLMs, RAG, and Generative AISoumia Chafi, Mustapha Kabil, Abdessamad KamoussThe digital transformation of Human Resources Information Systems (HRIS) requires advanced approaches to process unstructured textual data originating from Curriculum Vitae (CVs), cover letters, and job postings. Traditional text classification methods exhibit limitations when faced with current needs for contextual understanding and fine-grained skill detection. This paper proposes a hybrid pipeline combining advanced text classification, contrastive learning (SimCSE, Contriever), Retrieval-Augmented … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,509 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFuzzy Method for Online Learning of Bayesian Network ParametersMariana D.C. Lima, Silvia M. NassarIn learning problems, there are situations where training data is not fully available at the learning time. They are incrementally generated by time, defining a type of domain called online that has among its characteristics the possibility of data failure or even missing data. In Bayesian networks, learning is divided into two categories: structure (related to the graph of conditional … …Journal of Computer Science, Vol. 15, Issue 3 · 16 Mar 2019 · 7,498 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Distillation GAN Model for Network Intrusion DetectionChandrakala C B, Sai Sreevall, Raghudathesh G PThis study presents a distillation-based Generative Adversarial Network (GAN) model designed for intrusion detection in network systems. A Teacher-Student architecture is proposed, in which a single teacher generator is utilized to train both the teacher discriminator and the student discriminator. The model was trained to identify anomalies present in network traffic intrusions by tuning the min-max loss function in GANs. … …Journal of Computer Science, Vol. 22, Issue 2 · 5 Mar 2026 · 1,549 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Hybrid Machine and Deep Learning Model for Detecting Arabic Phishing EmailsFahad GhabbanPhishing emails are becoming an increasingly popular type of cybercrime on the internet, affecting both businesses and individuals. The attackers generally use various methods to trick victims and extract personal information from them, such as bank details, home addresses, and account information. Many attempts have been proposed to tackle this issue by using filtering mechanisms or automated classification methods which … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,897 accessesView PDFCite
Review ArticleOpen accessIn the keywordsA Survey of Generative AI ApplicationsRoberto Gozalo-Brizuela, Eduardo Eduardo Garrido MerchanGenerative AI has experienced remarkable growth in recent years, leading to a wide array of applications across diverse domains. In this study, we present a comprehensive survey of more than 350 generative AI applications, providing a structured taxonomy and concise descriptions of various unimodal and even multimodal generative AIs. The survey is organized into sections, covering a wide range of … …Journal of Computer Science, Vol. 20, Issue 8 · 24 May 2024 · 16,693 accessesView PDFCite
Research ArticleOpen accessIn the abstractVision Tune: A Deep Learning Framework for Sentiment Driven Video, Image and Music CreationLukesh Rameshpant Kadu, Manoj Deshpande, Vijaykumar PawarArtificial intelligence has enabled powerful generative models for text, images, video, and music, yet most tools still operate independently without a unified, multi-modal workflow. This article proposes an integrated AI framework, Vision Tune, that consolidates these isolated capabilities into a single, sentiment-aware platform for end-to-end media creation. The system leverages deep learning and multi-scope AI models to automatically generate written … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,496 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring University Students' Perceptions of AI Tools in Programming Education: An Extended TAM ApproachAreej Abdullah AlfuhaidGenerative Artificial Intelligence (AI) is commonly used in programming education. Tools such as ChatGPT and GitHub Copilot aid in code generation, debugging, and explanation. The benefits are clear, though concerns about learning quality and academic integrity persist.We tested an extended Technology Acceptance Model (TAM) for university programming courses. The model included perceived usefulness and perceived ease of use. It added … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 2,061 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,751 accessesView PDFCite