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Self-Driving Car Simulation using Adaboost-CNN Algorithm

Self-Driving Car Simulation using Adaboost-CNN Algorithm

Ali Mohammad Tarif, S. M. Raju, Mohammod Al Amin Ashik, Md. Shariful Islam, Tabassum Tahera

 

Verlag GRIN Verlag , 2018

ISBN 9783668611757 , 26 Seiten

Format PDF, OL

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Self-Driving Car Simulation using Adaboost-CNN Algorithm


 

Project Report from the year 2017 in the subject Engineering - Automotive Engineering, grade: 2.00, International Islamic University Malaysia, course: CSC 3304: Machine Learning, language: English, abstract: People spend hours to drive their car from place to place. What if a person sets its destination and goes to sleep while the car drives itself to the destination? It will save plenty of time. Tesla already started selling autopilot cars. Though the car can drive itself but is trustable only in certain quality roads. This means, research should still be carried out in self driving car project. All of the existing self-driving car simulation projects used Convolutional Neural Network as learning method. Though Adaboost is mostly used with binary classification problem, a variant can be developed to adapt Adaboost with Convolutional Neural Network.

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