fanap internship
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FANAP SUMMER INTERNSHIP1394
Hanzaleh Akbari Nodehi – EE 91
Ghazal Helmzadeh - CS 92
Alireza Amirshahi – EE 91
Pardis Pashakhanloo - CE 91
Pourya Mandi Sanam – EE 91
Amir Hossein Nazem – EE 91
OUR TEAM
INTERNSHIP: AN OPPORTUNITYOR just another wasted labor?
◦Getting hands dirty
◦Boosting skills
◦Broadening horizons
◦Dude, let me tell you something…real world is much bigger than university!
◦Realistic decisions based on real interests
DO YOU REMEMBER THE FIRST DAY YOU ENTERED THE UNIVERSITY?!
We started learning…
Open-Source Computer Vision Library
No more reinventing the wheel
OPENCV
Opencvmodules
core
imgproc
objdetect
video
ml
highgui
Opencv seems better:
• Money
• Speed & Performance
• Cross-platform
• Ease of Use
FACE DETECTION AND FEATURE EXTRACTION
FACE DETECTION
First approach: skin color
Machine learning… better job
PAUL VIOLA & MICHAEL JONES
WE NEED FEATURES…
MAIN IDEAPositive
And Negative Images
Extract feature
Integral image
Features with
minimum error
Weighted sum of
features
Cascade
OBJECT DETECTION
Ball Detection with opencvObject Detection Using Color
Edge Detection
Tracking Object
Let’s see …
Machine learning
In 1959, Arthur Samuel defined machine learning as a "Fieldof study that gives computers the ability to learn withoutbeing explicitly programmed".
Arthur Lee Samuel was an American pioneer in the field of computer gaming, artificialintelligence, and machine learning.Born: December 5, 1901, Emporia, Kansas, United StatesDied: July 29, 1990, Stanford, California, United StatesEducation: College of Emporia (1923), Massachusetts Institute of Technology
WHAT IS MACHINE LEARNING ?!!
without being explicitly programmed !!!
If (this expression is true) {code block
} Else {another code block
}
Let me explain it with examples …
How do we learn ?!!
Time …
???
. . .
That was four.
• Machine Learning on the other hand is writing aprogram that learns from past experience.
It’s Applications …You've probably use a learning algorithm. dozens of times a day without knowing it.
Web Engines Photo Tagging Applications Spam Filter…
Web Engines Photo Tagging Applications Spam Filter…
EVERY TIME YOU USE A WEB SEARCH ENGINES LIKE GOOGLE OR BING TOSEARCH THE INTERNET, ONE OF THE REASONS THAT WORK SO WELL IS BECAUSEA LEARNING ALGORITHM, ONE IMPLEMENTED BY GOOGLE OR MICROSOFT, HASLEARNED HOW TO RANK WEB PAGES.
It’s Applications …You've probably use a learning algorithm. dozens of times a day without knowing it.
Web Engines Photo Tagging Applications Spam Filter…
Web Engines Photo Tagging Applications Spam Filter…
EVERY TIME YOU USE FACEBOOK OR APPLE'S PHOTO TAGGING APPLICATIONAND IT RECOGNIZES YOUR FRIEND'S PHOTOS, THAT'S ALSO MACHINELEARNING.
It’s Applications …You've probably use a learning algorithm. dozens of times a day without knowing it.
Web Engines Photo Tagging Applications Spam Filter…
Web Engines Photo Tagging Applications Spam Filter…
EVERY TIME YOU READ YOUR EMAILS AND YOUR SPAM FILTER SAVES YOU FROMHAVING TO WADE THROUGH TONS OF SPAM EMAIL, THAT'S ALSO A LEARNINGALGORITHM.
Future …
For big companies like facebook, google, yahoo and …, one of the reasons they're excited is theAI dream of someday building machines as intelligent as you or me.
Reading a captcha
How to read a
C A P T C H A
What is captcha?An acronym for "Completely Automated Public Turing test to tell Computers and Humans Apart”
A CAPTCHA is a type of challenge-response test used in computing to determine whether or not the user is human.
What we have done?Different approaches to read characters automatically
Optical Character Recognition
Decision Tree
Neural Network
Template Matching
Etc.
What we have done? (Cont’d.)Developing a NN based program to automatically decipher a Captcha
Advantages of using Neural Networks (our approach) for character recognition
Robust against noise and change in font, size, etc.
Easily portable to other fonts, characters, and even languages.
NowLet’s
down a server!
Motion detection
Motion Detection – Simple Approach
Using a threshold◦Problem: most cameras produce noisy images
◦Solution: Erosion filter
Motion Detection – Common Approach
Compare frames◦Good idea with compression in mind◦Disadvantage: slow movement
Motion Detection – Better Approach
Change the way you compare◦Independent from motion speed◦Disadvantage: dealing with gone objects
Motion detection - Most Efficient Approaches
Based on building the background of the scene
THANKS!
the end