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12/17/2020
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Computer Vision Bootcamp with Python (OpenCV) - YOLO, SSD, computer vision training and image processing using Python language, OpenCV library and methods such as Viola-Jones, R-CNNs and more. Today, image processing, and especially face and object recognition (which is also the focus of this course) is one of the most popular topics in technology because these algorithms can be used in several fields, from software engineering to criminal investigation; For example, line detection methods in self-driving cars are highly dependent on computer vision and are one of its most common applications. With the advent of deep learning and GPUs in the last decade, it has even become possible to instantly implement these algorithms on live video.
This course deals with the theoretical training of face and object recognition algorithms and then applies them to various problems. You will first learn the theory of computer vision, filters and kernels (blur, sharpen and edge detection); Then, you will be introduced to the Canny algorithm and the Hough conversion for line recognition in self-driving cars and face recognition in images and videos, the Viola-Jones algorithm and the sliding window approach. In the next section, you will learn the HOG algorithm as a better alternative to Viola-Jones, gradients detection, histogram construction, and the use of the SVM machine learning algorithm. Twisted neural network-based methods (CNNs) include C-RNNs and their faster approaches, object recognition algorithms YOLO, IOU, SSD, and the VGG16 and MobileNet architectures.
Gain a proper understanding of the most powerful models of computer insight
Master the OpenCV library
Understand and implement Viola-Jones, HOG and YOLO algorithms
Mastering CNN-related approaches and implementing them
Familiarity with SDD algorithm
Complete mastery of face and object recognition
People who are interested in machine learning (artificial intelligence) and computer insight.
Publisher: Udemy
Instructor: Holczer Balazs
English language
Level of training: from basic to advanced
Number of lessons: 106 lessons in 19 sections
Duration: 9h 46m
Basic Python programming skills
After Extract, watch with your favorite Player.
English subtitle
Quality: 720p
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