A color vision approach considering Reflection Co efficient based on Autoencoder techniques using deep neural networks

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.

Description

Cataloged from PDF version of thesis.
Includes bibliographical references (pages 46-48).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.

Keywords

Auto Encoded Techniques, Reflection Co efficient, Neural networks, Deep learning, KNN, ANN, Random forest, Logistic regression, Naive bayes, Decision tree, Digital Illuminance meter

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