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Computer Vision and Image Recognition using AI

9,999.00

( 0 Review )

Course Level

Intermediate

Total Hour

60h

Video Tutorials

16

Course content

60h

Week 1: Introduction to Computer Vision and Image Processing

Overview of computer vision and its applications
Image representation and preprocessing techniques
Introduction to basic image processing operations (e.g., filtering, edge detection)
Hands-on exercises with OpenCV or similar library

Week 2: Convolutional Neural Networks (CNNs)

Week 3: Object Detection and Localization

Week 4: Advanced Topics in Computer Vision

About Course

Computer Vision and Image Recognition using AI courses provide an excellent opportunity to delve into the exciting field of visual understanding. These courses equip learners with the necessary skills and knowledge to tackle complex computer vision tasks, such as image classification, object detection, and image segmentation. By leveraging the power of deep learning and Convolutional Neural Networks (CNNs), these courses teach students how to extract meaningful features from images, understand their spatial relationships, and make accurate predictions. With a focus on practical applications, students gain hands-on experience in training models, leveraging pre-trained networks, and optimizing performance. These courses are designed to empower individuals with the expertise needed to develop cutting-edge solutions in industries like autonomous vehicles, healthcare, surveillance, and more. Whether you’re a beginner or an experienced practitioner, exploring Computer Vision and Image Recognition using AI courses can unlock a world of possibilities in visual data analysis and interpretation.

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What Will You Learn?

  • Fundamental concepts and techniques in computer vision
  • Image preprocessing and representation methods
  • Basic and advanced image processing operations
  • Convolutional Neural Networks (CNNs) for image classification
  • Transfer learning and fine-tuning pre-trained models
  • Object detection techniques and architectures
  • Image segmentation methods
  • Generative models for image synthesis
  • Recent advancements and emerging trends in computer vision
  • Practical skills using libraries like OpenCV and deep learning frameworks
  • Hands-on projects applying computer vision techniques to real-world problems

Material Includes

  • Live Classes 2Hr Daily
  • Flexibility
  • Accessible Learning Materials
  • Sharable Certificate

Instructor

AG
4.44 /5

78 Courses

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Material Includes

  • Live Classes 2Hr Daily
  • Flexibility
  • Accessible Learning Materials
  • Sharable Certificate

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