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Pluralsight

Object Detection Recognition and Tracking

via Pluralsight

Overview

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Computer vision applications can automate and enhance the analysis and interpretation of visual data
beyond human capabilities. This course will teach you how image classifiers can perform object detection recognition and tracking using Tensorflow.

Computer vision applications can automate and enhance the analysis and interpretation of visual data (images/videos) beyond human capabilities. In this course, Object Detection Recognition and Tracking, you’ll learn to create an image classifier using Tensorflow. First, you’ll explore how neural networks are used for image classification. Next, you’ll learn how to create an image classifier with different levels of accuracy. Finally, you’ll learn about three different types of neural networks. When you’re finished with this course, you’ll have the skills and knowledge of computer vision for object detection recognition and tracking needed to create an image classifier.

Syllabus

  • Course Overview 1min
  • Understanding How Neural Networks are Used for Image Classification 28mins
  • Understanding Advanced Neural Networks for Image Classification: ResNet, Inception, and MobileNets 10mins

Taught by

Xavier Morera

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