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Titlebook: Applied Machine Learning and Data Analytics; 6th International Co M. A. Jabbar,Sanju Tiwari,Tasneem Bano Rehman Conference proceedings 2024

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楼主: 威风
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,Process Selection for RPA Projects with MDCM: The Case of Izmir Bakircay University,tant for public universities as it helps streamline administrative processes, improve operational efficiency, and free up staff resources, allowing the institutions to focus more on delivering quality education and enhancing the overall student experience. However, selecting the right processes for
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,Data-Driven Approach to Network Intrusion Detection System Using Modified Artificial Bee Colony Algwork using the Artificial Bees Colonization Algorithm. A self-driven metric has been defined to determine the performance of a network that would detect the behavior of its nodes. This algorithmic metric is inspired by the Nature-Inspired Artificial Bees Colonization Algorithm. The end result is ran
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An Efficient Image Dehazing Technique Using DSRGAN and VGG19,ss the issue of haze, image dehazing has become an area of significant importance. However, many current techniques for unsupervised picture dehazing rely on simplified atmospheric scattering models and a priori knowledge, which can result in inaccuracies and poor dehazing performance. The study of
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Benchmarking ML and DL Models for Mango Leaf Disease Detection: A Comparative Analysis,rate detection of these diseases is crucial for enabling timely interventions and enhancing crop management strategies. In this study, we conduct a comprehensive comparison of various ML and DL models to effectively detect and classify common mango leaf diseases, as well as to differentiate between
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Cassava Syndrome Scan a Pioneering Deep Learning System for Accurate Cassava Leaf Disease Classificces threats from a variety of leaf diseases, leading to substantial reduction in yield. Prompt and precise identification of these diseases is essential for implementing effective countermeasures and maintaining adequate food supply. Recently, deep learning methodologies have demonstrated remarkable
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DESI: Diversification of E-Commerce Recommendations Using Semantic Intelligence,ramework, which is a query-driven, semantically oriented, Web 3.0 conforming ecommerce recommendation framework. The pre-process query was enriched using the Latent Semantic Indexing. Ontologies are generated from the ecommerce product dataset. The classification of the metadata takes place using th
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