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Development Data Science Deep Learning

Object Recognition with Deep Learning using OpenCV and C#

Building Object Detection and Classification Applications using Computer Vision, Deep Learning, OpenCV and C#
Rating: 3.9 out of 53.9 (17 ratings)
124 students
Created by F. Frank Ozz
Last updated 1/2021
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Object Classification and Detection from images using Deep Learning, Computer Vision and C# Programming Language

Course content

3 sections • 11 lectures • 1h 21m total length

  • Preview00:21
  • Preview03:18

  • Preview10:22
  • Preview04:59
  • Chapter 1.2 How are Neural Networks Trained- Overview
    07:58

  • Preview08:27
  • Chapter 2.2 Procedure for object classification and files required, DNN module
    04:46
  • Chapter 2.3 Object Classification Implementation
    19:22
  • Chapter 2.4.0 Object Detection Intro
    04:02
  • Chapter 2.4.1 Object Detection Application Development
    11:59
  • Chapter 2.4.3 Yolov2 Intro
    05:40

Requirements

  • Some C# programming Skills
  • My Computer Vision Fundamentals with OpenCV and C# course

Description

  1. This course is the first course in its field using C# programming language and OpenCV Deep Learning Module to teach you to develop object detection or recognition applications using Deep learning techniques


  2. This course is going to teach you

    • How to develop Object Recognition Applications from images ( either static or webcam/video)  using popular computer vision library OpenCV, its Deep learning Module and C# Programming Language


    • Overview of how Neural Networks detect objects from images


    • Overview of   what Convolutional Neural Networks mean and how they are trained to detect objects from images


    • Overview of ImageNet image recognition competition, base image detection frameworks ( VGG, SSD, GoogLeNet)


    • Types of object detection frameworks such as YOLO, Caffe, DarkNet


    • You will be able to develop object classification and detection using Caffe and DarkNet framework models:


      • We'll be creating an object classification application using Caffe framework and GoogleNet base's framework that can distinguish between 1000 objects.


      • We'll be creating an object detection application using MobileSSD base and Caffe framework which can detect and label objects if they belong to any of the 80 different classes of objects and their probability of match.


      • We'll be converting the object detection application to an app which can work on webcam images  or video streams in real-time(To be uploaded by next week)


      • We'll be using DarkNet framework and YOLO(You Only Look Once) algorithm  v2 to detect images in real-time for faster results(To be uploaded by next week)

    • Enjoy the course!

Who this course is for:

  • C# developers wanting to develop Deep Learning Computer Vision applications

Instructor

F. Frank Ozz
Software Architect, Author
F. Frank Ozz
  • 4.0 Instructor Rating
  • 759 Reviews
  • 3,634 Students
  • 6 Courses

I have been working in software development industry   as an architect and teacher totaling  12 years now.  Prior to that I had been working  in automotive manufacturing industry for over 15 years  as management professional.  I have a  BSc degree  in Textile Machinery Engineering    from the Leeds University in the UK  and  also an MSc  degree in Software Engineering . I have been teaching mainly software development   with .NET  and JAVA  technologies to various student groups from banking software developer personnel to  IT development company engineers at software institutions.

I am the author of a book published in the UK on developing "Practical Image Processing" projects with C# Programming Language.

I have also good experience in  electronics and robotics    and  designed and built many mechatronics involved  testing equipment for the plants I worked.  

Nowadays I am very much into designing and building applications using dockerized microservices with aspnetcore.


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