Advanced Computer Vision

Computer Vision takes a fascinating glimpse into the future of machine learning.It basically evolves a bunch of convolutional neural networks using a genetic algorithm to create an optimal network for image classification.

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About the course

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Computer vision has become prevalent in our society with its applications spanning across multiple domains like medicine, mapping, drones, and self-driving cars. New developments in the neural network field have drastically improved the speed at which these images are processed and the performance of these state-of-the-art visual recognition systems.

With the knowledge of how to build a convolutional neural network and transfer learning, the advanced computer vision course builds on its foundation to make sure that you learn object detection, face detection and recognition using CNNs.

Skills you will gain

  • Semantic segmentation
  • UNet
  • Siamese Networks
  • Triplet loss

Course Syllabus

Module 1

Advanced Computer vision

3.5 Hrs

1 Quiz
  • Semantic Segmentation process
  • U-Net Architecture for Semantic Segmentation
  • Other variants of Convolutions
  • Inception and Mobile Net models
  • CNNs at Work - Object Detection with region proposals
  • CNNs at Work - Object Detection with Yolo and SSD
  • Hands-on demo- Bounding box regressor
  • Metric Learning
  • Siamese Netwrok as metric learning
  • How to train a Neural Network in SIamese way
  • Show more


Facial recognition system

Course certificate

Get Advanced Computer Vision course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.