Advanced Certificate in Computer Vision Fundamentals: Basics
-- ViewingNowThe Advanced Certificate in Computer Vision Fundamentals: Basics is a comprehensive course designed to equip learners with essential skills in computer vision. This certificate course focuses on the basics of computer vision, including image processing, feature detection, and object recognition.
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⢠Introduction to Computer Vision – Understanding the basics of computer vision, its applications, and challenges.
⢠Image Processing – Learning about image processing techniques, including filtering, edge detection, and image transformations.
⢠Feature Extraction – Exploring feature extraction methods, such as scale-invariant feature transform (SIFT), speeded-up robust features (SURF), and histogram of oriented gradients (HOG).
⢠Convolutional Neural Networks (CNN) – Understanding the structure and functionality of CNNs, including their application in image classification and object detection.
⢠Object Detection – Learning about object detection techniques, including sliding window, region proposal networks (RPN), and you only look once (YOLO) algorithm.
⢠Semantic Segmentation – Exploring semantic segmentation techniques, such as fully convolutional networks (FCN) and U-Net.
⢠Deep Learning Fundamentals – Understanding the basics of deep learning, including activation functions, backpropagation, and optimization techniques.
⢠3D Computer Vision – Learning about 3D computer vision techniques, including stereo vision, structure from motion (SfM), and simultaneous localization and mapping (SLAM).
⢠Evaluation Metrics – Understanding evaluation metrics used in computer vision, such as intersection over union (IoU), mean average precision (mAP), and receiver operating characteristic (ROC) curve.
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