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Artificial intelligence for vision applications
ARTIFICIAL INTELLIGENCE:
• Artificial Intelligence is a way of making a computer, a computer-
controlled robot, or a software think intelligently, in the similar
manner the intelligent humans think.
• AI is accomplished by studying how human brain thinks, and how
humans learn, decide, and work while trying to solve a problem, and
then using the outcomes of this study as a basis of developing
intelligent software and systems.
“HUMAN REACTION IS
THE UNLTIMATE GOAL
FOR AI”
Artificial intelligence for vision applications
COMPUTER VISION
Artificial intelligence for vision applications
Artificial intelligence for vision applications
OBJECT DETECTION:
• Object detection is a computer
technology related to computer
vision and image processing that
deals with detecting instances of
semantic objects of a certain
class (such as humans, buildings,
or cars) in digital images and
videos.
Artificial intelligence for vision applications
Artificial intelligence for vision applications
FACIAL RECOGNITION:
Used for:
• Identification
• Surveillance
• Bimetric Security
Artificial intelligence for vision applications
Artificial intelligence for vision applications
AUTONOMOUS NAVIGATION:
• Used in self driving vehicles to
navigate around the streets
without any human
intervention.
• It uses cameras and sensors all
around the vehicle to track and
locate objects in order to
navigate around them.
Artificial intelligence for vision applications
Artificial intelligence for vision applications
Artificial intelligence for vision applications
ADVERSARIAL LEARNING:
• Machine Learning technique used to improve the result of an AI
model using another malicious AI model.
Simulating future moments from an input image:
Artificial intelligence for vision applications
IMAGE RECOGNITION:
• Image recognition, in the context of machine vision, is the ability of
software to identify objects, places, people, writing and actions in
images.
• Computers can use machine vision technologies in combination with
a camera and artificial intelligence software to achieve image
recognition.
Artificial intelligence for vision applications
Artificial intelligence for vision applications
“IN THIS FIELD, AI IS PROVEN TO
BE BETTER THAN HUMANS”
Artificial intelligence for vision applications
DEEPFAKES:
• Itis an artificial intelligence-based human image synthesis technique.
It is used to combine and superimpose existing images and videos
onto source images or videos using a machine learning technique
called a "generative adversarial network" (GAN).
• The combination of the existing and source videos results in a fake
video that shows a person or persons performing an action at an
event that never occurred in reality.
CAPTCHA:
• It is a type of challenge–
response test used in computing
to determine whether or not the
user is human.
CONCLUSION:
• In conclusion, I’d like to state that it is very exciting to see such
amazing advancements in Artificial Intelligence. It is only going to get
better in the future and I am personally very sure that AI will play a
very vital role in our day to day lives. We will eventually depend on
computers to perhaps find cancers in our bodies and help the blind to
finally see the world. We must provide our avid support towards this
cause.
Thank You!!!
Any Queries?

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Artificial intelligence for vision applications

  • 2. ARTIFICIAL INTELLIGENCE: • Artificial Intelligence is a way of making a computer, a computer- controlled robot, or a software think intelligently, in the similar manner the intelligent humans think. • AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.
  • 3. “HUMAN REACTION IS THE UNLTIMATE GOAL FOR AI”
  • 8. OBJECT DETECTION: • Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.
  • 11. FACIAL RECOGNITION: Used for: • Identification • Surveillance • Bimetric Security
  • 14. AUTONOMOUS NAVIGATION: • Used in self driving vehicles to navigate around the streets without any human intervention. • It uses cameras and sensors all around the vehicle to track and locate objects in order to navigate around them.
  • 18. ADVERSARIAL LEARNING: • Machine Learning technique used to improve the result of an AI model using another malicious AI model.
  • 19. Simulating future moments from an input image:
  • 21. IMAGE RECOGNITION: • Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in images. • Computers can use machine vision technologies in combination with a camera and artificial intelligence software to achieve image recognition.
  • 24. “IN THIS FIELD, AI IS PROVEN TO BE BETTER THAN HUMANS”
  • 26. DEEPFAKES: • Itis an artificial intelligence-based human image synthesis technique. It is used to combine and superimpose existing images and videos onto source images or videos using a machine learning technique called a "generative adversarial network" (GAN). • The combination of the existing and source videos results in a fake video that shows a person or persons performing an action at an event that never occurred in reality.
  • 27. CAPTCHA: • It is a type of challenge– response test used in computing to determine whether or not the user is human.
  • 28. CONCLUSION: • In conclusion, I’d like to state that it is very exciting to see such amazing advancements in Artificial Intelligence. It is only going to get better in the future and I am personally very sure that AI will play a very vital role in our day to day lives. We will eventually depend on computers to perhaps find cancers in our bodies and help the blind to finally see the world. We must provide our avid support towards this cause.