It takes the average reader and 26 minutes to read Self-Driving Car Simulation using Adaboost-CNN Algorithm by Ali Mohammad Tarif
Assuming a reading speed of 250 words per minute. Learn more
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.
Self-Driving Car Simulation using Adaboost-CNN Algorithm by Ali Mohammad Tarif is 26 pages long, and a total of 6,656 words.
This makes it 9% the length of the average book. It also has 8% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes and 36 minutes to read Self-Driving Car Simulation using Adaboost-CNN Algorithm aloud.
Self-Driving Car Simulation using Adaboost-CNN Algorithm is suitable for students ages 8 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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