Computer Vision Bootcamp™ with Python (OpenCV) - YOLO, SSD | Computer Vision course 82% off


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

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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