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22 results for “Regularization”
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Research ArticleOpen accessIn the keywordsEstimate Polluting AgentsAbdelhani BoukroucheThe concentration estimation of hydrocarbons not burned emitted in smokes by a boiler during its beginning will be discussed in the present investigation. The objective is to verify if the boiler is conform to European norms; so that a recorded data processing has been achieved with a restoration method based on the use of two regularization parameters resulting in the … …American Journal of Environmental Sciences, Vol. 4, Issue 4 · 31 Aug 2008 · 6,337 accessesView PDFCite
Research ArticleOpen accessIn the keywordsLogistic Regression with Multi-Connected WeightsAvazjon Marakhimov Rakhimovich, Kabul Khudaybergenov Kadirbergenovich, Zahriddin Muminov Ishkobilovich, Kudaybergenov Jabbarbergen KadirbergenovichResults of current research in biological and cognitive science reveal that neuronal interactions predominantly depend on neurotransmitters for signaling and sending information between neurons. Furthermore, a specific neuron that is connected to the next neuron transmits or sends multiple neurotransmitters in parallel ways, where each neurotransmitter has specific functional roles. Based on these results, a new type of logistic regression … …Journal of Computer Science, Vol. 20, Issue 9 · 4 Jul 2024 · 5,059 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzyNET: A Fuzzy Logic-Based Framework for Enhancing Urban Efficiency in Smart CitiesHemant Kumar, Safdar Tanweer, Parul Agarwal et al.The smart city paradigm emphasizes the strategic use of IoT, Big Data, and digital technologies to optimize urban operations and improve service delivery for citizens. Embedding digital technologies within operational workflows is driven by the objective of improving efficiency and long-term sustainability. The core transformation is Artificial Intelligence (AI) that revolutionizes management of cities through automation and instantaneous decisions based … …Journal of Computer Science, Vol. 22, Issue 7 · 19 Jul 2026 · 820 accessesView PDFCite
Review ArticleOpen accessIn the abstractAI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future DirectionsEmrobowansan Monday IdamokoroArtificial Intelligence (AI) is revolutionizing the meat sector by improving efficiency, accurateness, as well as sustainability in meat production, quality evaluation, and safety control. The conventional systems of meat inspection, handling, and processing are usually time consuming, labour-intensive, prone to contamination during handling and often susceptible to human errors. The use of artificial intelligence to drive technologies, including Deep Learning … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 3,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Intelligence and Mathematical Modelling-Based Techniques to Improve Social Media MarketingKiran Chaudhary, Mohammad Naquibur Rahman, Nabeela Hasan et al.The Businessperson is using social media to do marketing of their product. Almost all people use social media. Most people relate to social media. Social media marketing is beneficial in making the product more popular and easy ways to introduce the product to everyone in economical ways. In this study, we introduce the concept of machine learning and mathematical models … …Journal of Computer Science, Vol. 21, Issue 1 · 5 Dec 2024 · 5,478 accessesView PDFCite
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractCapsule Defect Detection and Classification Using Enhanced MobileNet ModelWenqing Bian, Yongzhi Huang, Baolian Shan, Yanting ChangThe quality of capsules has a direct impact on human health. However, defects inevitably arise during the capsule manufacturing process, and manual sorting is required. Most studies on capsule defects focus on detecting surface imperfections and those on internal capsule defects remain relatively limited. This study classifies four types of capsules using the deep learning model MobileNet, aiming to accurately … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 4 · 5 Nov 2024 · 5,203 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 abstractImage Super-Resolution using Auto-Encoders with Parallel Skip-ConnectionsLisha Pulickal Purushothaman, Jayasree Vadakke KadangoteSuper-resolutionimages are highly desired when employed for numerous analytical purposes andobviously because of their superior attractive visual effect. To create aHigh-Resolution (HR) image from one or more Low-Resolution (LR) images, animage super-resolution technique is used. When dealing with naturalenvironments and settings, it is not always easy to access high-resolutionimages. The main barriers to the same are limitations in acquisition methods.In … …Journal of Computer Science, Vol. 18, Issue 11 · 11 Nov 2022 · 6,081 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalyzing Effect on Residual Learning by Gradual Narrowing Fully-Connected Layer Width and Implementing Inception Block in Convolution LayerSaurabh SharmaResearch conducted on the advancement of CNN architecture for computer vision problems focuses on strategically choosing and modifying convolution hyperparameters (kernel, pooling, etc.). However, these research works don't exploit the advantage of employing multi fully-connected layers post the core schema to avail further performance improvements, which have been identified as the first research gap. Studies were also conducted to address … …Journal of Computer Science, Vol. 18, Issue 5 · 24 May 2022 · 6,044 accessesView PDFCite