The image classification for vehicles has vast application in automating cars and transportation. The images we have for training data set was from the driver’s point of view while driving the car. The images were taken as original frames extracted from different videos of local traffic of Lahore. The image classification for vehicle as an object for detection has been done using 2 separate approaches. Both of the approaches have their own merits and demerits which can vary with the application and purpose of its use.

1. Computer Vision
Self Driving Car: Classifying Vehicle Properties
Adeel Ahmed
BSEE-13043
Muhammad Jamal
BSEE-13024
M. Abdul Wajid
BSCS-14054

2. Classifying Vehicle Properties
This Project Aims to Train a Deep Learning Based Model That Will
Help In Making Self Driving Cars for the Local Environment.

3. Classifying Vehicle Properties
Image Set of 13193 Images from which we had to extract 4 different
categories of vehicles from driver perspective.
• Rickshaw
• Qingchis
• Motorbikes which further are classified as
1. One person sitting
2. More than one person sitting on the motorbike.

7. Classifying Vehicle Properties
VGG
Without VGG
Version 2 Keras VGG 16

18. Classifying Vehicle Properties
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19. Classifying Vehicle Properties
We have Developed a Good Deep Learning Algorithm for
Classifying Vehicle Properties. We Have Worked on Two
Different Schemes And Have Observed Two Very Unique
Outcomes Depending on Labels. Our Best Classifier Is Giving Us
Approximately 87% Accuracy Which is Good Because Our Data
Was Not Enough.

20. Anyref Jamal Edit here
[Cite Here]

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