Computer Vision with Python 3
4.4
(7 reviews total)
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Introduction to Image Processing
- Introduction to Image Processing
- Image processing - its applications
- Image processing libraries
- Summary
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Filters and Features
- Filters and Features
- Image derivatives
- Convolution
- Understanding image filters
- Edge detection
- Summary
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Drilling Deeper into Features - Object Detection
- Drilling Deeper into Features - Object Detection
- Revisiting image features
- Harris corner detection
- Local Binary Patterns
- Oriented FAST and Rotated BRIEF (ORB)
- Image stitching
- Summary
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Segmentation - Understanding Images Better
- Segmentation - Understanding Images Better
- Introduction to segmentation
- Contour detection
- The Watershed algorithm
- Superpixels
- Normalized graph cut
- Summary
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Integrating Machine Learning with Computer Vision
- Integrating Machine Learning with Computer Vision
- Introduction to machine learning
- Applications of machine learning for computer vision
- Logistic regression
- Support vector machines
- K-means clustering
- Summary
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Image Classification Using Neural Networks
- Image Classification Using Neural Networks
- Introduction to neural networks
- Convolutional neural networks
- Challenges in machine learning
- Summary
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Introduction to Computer Vision using OpenCV
- Introduction to Computer Vision using OpenCV
- Installation
- OpenCV APIs
- Summary
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Object Detection Using OpenCV
- Object Detection Using OpenCV
- Haar Cascades
- Scale Invariant Feature Transformation (SIFT)
- Speeded up robust features
- Summary
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Video Processing Using OpenCV
- Video Processing Using OpenCV
- Reading/writing videos
- Basic operations on videos
- Color tracking
- Object tracking
- Summary
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Computer Vision as a Service
- Computer Vision as a Service
- Computer vision as a service – architecture overview
- Environment setup
- Developing a server-client model
- Computer vision engine
- Putting it all together
- Summary