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Showing 41 - 60 results of 133 for search '(functional OR function) (link OR like) artificial neural network', query time: 0.25s Refine Results
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    THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

    Published 2025-03-01
    “…Deep learning, especially deep convolutional neural networks (CNNs), has become a prominent approach, mimicking brain functions to process images through multiple layers. …”
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    Numerical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm by Ying-Chun CHANG, Min-Chie CHIU, Meng-Ru WU

    Published 2018-07-01
    “…Here, the objective function can be established by using Artificial Neural Networks (ANNs) in conjunction with the muffler’s design parameters and related TLs (simulated by FEM). …”
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  11. 51

    Noise Elimination of Reciprocating Compressors Using FEM, Neural Networks Method, and the GA Method by Ying-Chun CHANG, Min-Chie CHIU, Ji-Lin XIE

    Published 2017-04-01
    “…Additionally, to facilitate the shape optimization of the muffler, a polynomial neural network model is adopted to serve as an objective function; also, a Genetic Algorithm (GA) is linked to the OBJ function. …”
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    Neural network models for diagnosing recurrent aphthous ulcerations from clinical oral images by R. Raja Subramanian, R. Raja Sudharsan, Bavithra Vairamuthu, Deshinta Arrova Dewi

    Published 2025-08-01
    “…Our research focuses on the advanced classification of oral ulcer stages using a convolutional neural network (CNN). To evaluate performance comprehensively, we developed and tested three custom models, comparing their effectiveness in distinguishing between different stages of oral ulcers. …”
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    Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approach by Ajit Kumar Rout, P.K. Dash, Rajashree Dash, Ranjeeta Bisoi

    Published 2017-10-01
    “…The paper presents a low complexity recurrent Functional Link Artificial Neural Network for predicting the financial time series data like the stock market indices over a time frame varying from 1 day ahead to 1 month ahead. …”
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