Its a car detection slide from one of my car detection AI project explanation.

1. CAR DETECTION
CAR DETECTION

2. WHAT IS CAR DETECTION?
Vehicle detection process on road are used for vehicle
tracking, counts, average speed of each individual vehicle,
traffic analysis and vehicle categorizing objectives and
may be implemented under different environments changes.
WHAT IS CAR DETECTION?
WHAT IS CAR DETECTION?

3. METHODOLOGY :
METHODOLOGY :
YOLO ("you only look once") is a popular algorithm
because it achieves high accuracy while also being
able to run in real-time, almost clocking 45 frames
per second. It’s a deep convolutional neural network.

4. DATASET
DATASET
 Training Images
 Testing Images
 Sample Submission
 Training Images
 Testing Images
 Sample Submission

5. WORKING PROCEDURE
WORKING PROCEDURE
The YOLO algorithm works by dividing the image
into N grids, each having an equal dimensional
region of SxS. Each of these N grids is responsible
for the detection and localization of the object it
contains.

6. FUTURE WORK
FUTURE WORK
Model based detection.
Category based detection.
Model based detection.
Category based detection.

7. OUTCOME
OUTCOME
 Car detection
 Similar Vehicle detection
For using YOLO algorithm, the accuracy of this project is up to 98% via small
dataset experiment.

8. LACKINGS
LACKINGS
 Cannot detect multiple car so far
 Model based detection is not functional
 Category based detection is not available

9. REFERENCE
REFERENCE
Dataset - https://www.kaggle.com/code/serhanayberkkl/car-detection-rcnn-acc-
97/data
Yolo definitions - https://www.v7labs.com/blog/yolo-object-detection
Project link - https://colab.research.google.com/drive/1Yp-
KFp8xvlqFweSLLmYEOxLttcFigkaM?usp=sharing

10. THANK YOU
THANK YOU
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