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31 results for “generative model”
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Review ArticleOpen accessIn the abstractThe Impact of Di-2-Ethylhexyl Phthalate (DEHP) in Focus on the Reproductive System and Toxicity in Rat or Mammalian ModelVenkataramanaiah Poli, Srinivasulu Reddy MotireddyAbsalan, F., Saremy, S., Mansouri, E., Moghadam, M. T., Moghadam, A. R. E., & Razie, G. (2016). Effects of Mono-(2-Ethylhexyl) Phthalate and Di-(2-Ethylhexyl) Phthalate Administrations on Oocyte Meiotic Maturation, Apoptosis and Gene Quantification in Mouse Model. Cell Journal, 18(4), 503–513. https://doi.org/10.22074/cellj.2016.4717 Acevedo‐Rodriguez, A., Kauffman, A. S., Cherrington, B. D., Borges, C. S., Roepke, T. A., & Laconi, M. (2018). Emerging … …American Journal of Pharmacology and Toxicology, Vol. 19, Issue 1 · 6 Jun 2024 · 12,990 accessesView PDFCite
Review ArticleOpen accessIn the abstractA 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 abstractA 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 abstractWhale Optimized Deep Generative Adversarial Network Based Alzheimer's Stages Detection Using 3D MRI Brain NeuroimagingR. Sampath, M. BaskarAlzheimer's Disease (AD), a common, chronic neurodegenerative condition, is characterized by the loss of neurons and synapses in the cerebral cortex and specific subcortical regions. According to claims from a recent study, AD has a 20% misdiagnosis rate. Therefore, it is essential to create a useful tool to recognize the stages of AD with a lower prediction error rate to … …Journal of Computer Science, Vol. 19, Issue 8 · 4 Aug 2023 · 5,544 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Data Enhancement Method Based on Generative Adversarial Networks for Soybean Leaf Disease IdentificationXiao Yu, Cong Chen, Qi Gong, Lina LuSoybean leaf disease data collection is an expensive and time-consuming task. Convolutional neural network training requires a large amount of data, but traditional data enhancement methods (such as rotation, flipping, translation) are restricted by fixed rules and cannot generate images with diversity and variability. Aiming at the problem of the lack of soybean leaf disease data set, this study proposes … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 4 · 26 Nov 2022 · 5,207 accessesView PDFCite
Research ArticleOpen accessIn the abstractGrasshopper Optimization Algorithm-Generative Adversarial Network for Lung Cancer Detection and ClassificationSukruth Gowda, A JayachandranLung cancer is one of the most dangerous deadly diseases for individuals worldwide. Thus, the survival rate is low due to the difficulty in detecting lung cancer at advanced stages like symptoms; thus, prominence for early diagnosis is important. The detection and treatment of lung cancer is having great importance for early diagnosis. The existing Convolution Neural Network (CNN) based … …Journal of Computer Science, Vol. 18, Issue 3 · 9 Apr 2022 · 6,575 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock price prediction using Generative Adversarial NetworksHungChun Lin, Chen Chen, GaoFeng Huang, Amir JafariDeep learning is an exciting topic. It has been utilized in many areas owing to its strong potential. For example, it has been widely used in the financial area which is vital to the society, such as high-frequency trading, portfolio optimization, fraud detection and risk management. Stock market prediction is one of the most popular and valuable areas in finance. … …Journal of Computer Science, Vol. 17, Issue 3 · 2 Apr 2021 · 17,700 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrototyping Rule-Based Expert Systems with the Aid of Model TransformationsAlexander Yurievich Yurin, Nikita Olegovich Dorodnykh, Olga Anatolievna Nikolaychuk, Maksim Andreevich GrishenkoThe problem of improving efficiency of intelligence systems engineering remains a relevant topic of scientific research. One of the trends in this area is the use of the principles of cognitive (visual) modelling and design as well as approaches based on generative programming and model transformations. This paper aims to describe the implementation and application of model transformations for prototyping … …Journal of Computer Science, Vol. 14, Issue 5 · 3 Apr 2018 · 8,149 accessesView PDFCite
Research ArticleOpen accessIn the abstractCommon Metamodel of Component Diagram and Feature Diagram in Generative ProgrammingMatija Novak, Ivan Magdalenić, Danijel RadoševićComponent-based software engineering and generative programming are common approaches in software engineering. Each approach has some benefits and domain of usage. Component-based development is used to build autonomous components that can be further combined in different ways, while generative programming is more suitable when building systems that have different variants. Before a variable component based system can be build, it … …Journal of Computer Science, Vol. 12, Issue 10 · 15 Dec 2016 · 7,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving the Performance of Multivariate Bernoulli Model based Documents Clustering Algorithms using Transformation TechniquesPerumal Pitchandi, Nedunchezhian RajuProblem statement: Document clustering is the most important areas of data mining since they are very much and currently the subject of significant global research since such areas strengthen the enterprises of web intelligence, web mining, web search engine design and so forth. Generative models based on the multivariate Bernoulli and multinomial distributions have been widely used for text classification. … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,281 accessesView PDFCite