20 Hours Instructor Led Live Training | 20 Hours of Self Learning Labs | Five Assessments | CPE Credits | Certification on Completion
This course leading to certification will explore the principles and techniques used in real-world computer vision systems and the research and development of new systems. The module will cover image processing fundamentals, basics and applications of digital image processing, intensity transformations and colour image processing, image filtering and advanced image processing methods, spatial image filtering, image features, feature matching, texture matching, image segmentation, clustering images, classification of images, video analytics, and more. At the end of this course, the participants will understand and master essential knowledge, theories, and methods in image processing and computer vision.
What you will learn
- Introduction to Artificial Intelligence and Computer Vision
- Image processing, Computer vision, image formation, filtering, sampling, aliasing, frequency domain analysis, Fourier transforms, image transforms, background subtraction, Haar cascades, HOG transforms.
- Unsupervised learning for image processing, K-means, PCA, Object detection with background subtraction, Histogram based classification, image compression, Image classification,
- Face detection, recognition and verification, emotion detection, Supervised learning, feature engineering, image classification with deep neural networks.
- CNN, R-CNN, pre-trained models, video analysis, depth detection
