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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    A color vision approach considering Reflection Co efficient based on Autoencoder techniques using deep neural networks

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    17101269, 17101178, 17101276, 17101171_CSE.pdf (2.872Mb)
    Date
    2021-09
    Publisher
    Brac University
    Author
    Mahmud, Shakib Izaz
    Shovon, Sartaz Islam
    Hasnat, Md. Abrar
    Na s, Md. Fahim
    Metadata
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    URI
    http://hdl.handle.net/10361/17125
    Abstract
    Color vision approach using auto encoded technique is an effective way to detect objects. This approach considers various factors like movement detection, size and shape detection, color detection etc. Here we have considered reflection co efficient as another parameter to detect object material in different ambient lighting conditions. We are proposing to use deep learning methods to train our AI from values of light intensity of different objects in many controlled environments using digital illuminance meter also deep learning architecture on image data for detecting surface reflectance.
    Keywords
    Auto Encoded Techniques; Reflection Co efficient; Neural networks; Deep learning; KNN; ANN; Random forest; Logistic regression; Naive bayes; Decision tree; Digital Illuminance meter
     
    LC Subject Headings
    Cognitive learning theory (Deep learning); Neural networks (Computer science)
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 46-48).
    Department
    Department of Computer Science and Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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