Computer Vision Bootcamp™ with Python (OpenCV) - YOLO, SSD| Data Science Computer Vision course 82%off
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| Computer Vision Bootcamp™ with Python (OpenCV) - YOLO, SSD |
Description
This path is as regards the integral idea of picture processing, focusing about face discovery or objective detection. permanency These matters are getting altogether warm in modern times due to the fact this learning algorithms execute keep ancient among several fields beside software program engineering in imitation of iniquity investigation. durability Self-driving cars (for instance lane detection approaches) depends closely on pc vision.
With the creation of extreme lesson or vivid technology gadgets (GPUs) between the previous decade it is emerge as possible according to conduct these algorithms also within real-time videos. So where are ye running in conformity with learn among that course?
Section 1 - Idea Processing Fundamentals:
computer imaginative and prescient theory
what are pixel intensity values
convolution yet kernels (filters)
blur kernel
sharpen kernel
edge detection into computer vision (edge detection kernel)
Section 2 - Serf-Driving Cars yet Lane Detection
how in accordance with use laptop imaginative and prescient techniques within lane detection
Canny's algorithm
how after usage Hough seriously change in conformity with locate lines based over pixel intensities
Section three - Face Detection along Viola-Jones Algorithm:
Viola-Jones strategy in pc vision
what is sliding-windows approach
detecting faces of images then of videos
Section four - Histogram of Oriented Gradients (HOG) Algorithm
how to fail Viola-Jones algorithm including better approaches
how according to detects gradients then edges of an image
constructing histograms of oriented gradients
using assist vector machines (SVMs) as underlying machine lesson algorithms
Section 5 - Convolution Neural Networks (CNNs) Based Approaches
what is the hassle together with sliding-windows approach
region proposals or selective ask algorithms
region based convolutional neural networks (C-RNNs)
fast C-RNNs
faster C-RNNs
Section 6 - You Only Look Once (YOLO) Object Detection Algorithm
what is the YOLO approach?
constructing bounding boxes
how in conformity with discover objects in an photograph including a odd look?
intersection regarding union (IOU) algorithm
how according to hold the nearly relevant bounding field together with non-max suppression?
Section 7 - Single Shot MultiBox Detector (SSD) Object Detection Algorithm SDD
what is the principal idea behind SSD algorithm
constructing anchor boxes
VGG16 then MobileNet architectures
implementing SSD including real-time videos
We intention discuss in relation to the theoretical background over back awareness algorithms yet target discovery among the major below we are running in imitation of implement this troubles over a step-by-step basis.
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