Vue, View 100-minute core lecture

Machine learning, deep learning are now in practice!

The hottest field in artificial intelligence, Computer Vision!

Meet the Internet of Things IoT Raspberry Pi

It was born as a practical project.

Internet of Things and Deep Learning in the Computer Vision Field

Learn how to use it and see examples.

🗒 Course Introduction

While it is important to build a theoretical foundation while learning and teaching artificial intelligence, machine learning, and deep learning, I thought it was also important to develop the ability to apply it in practice.

So, we prepared a project that utilizes Internet of Things (IoT) devices in the field of Computer Vision, a representative field that uses artificial intelligence, machine learning, and deep learning .

Create a fun and useful project using the various image and video processing techniques and modules learned in the course '[OpenCV] Python Deep Learning Image Processing Project - Find Son Heung-min!'

 

This project recognizes handwritten text and lays the foundation for Computer Vision and Deep Learning.

You will practice various Internet of Things technologies while transferring the project to a Raspberry Pi IoT device.

The number of parked vehicles is counted by a parking lot camera and reported in real time to a cloud server.

Recognize the letters and numbers on your car license plate using the latest text recognition technology.

Check if you are dozing off with a real-time camera and wake up with an alarm if you are.

Install a Raspberry Pi surveillance camera to recognize the registered user's face and check the entry and exit details via the server, Dropbox, or email.

The lectures are structured so that you can learn fun tasks step by step along with the theory.

After completing the course, you will dream of various Computer Vision Deep Learning projects and businesses.

It also helped me a lot in preparing for the project I'm currently working on.

While creating this course, we developed various contents that were not included in the course, such as 'Counting the number of entrants', 'Counting the number and speed of vehicles', 'Identifying age and gender by looking at faces', and 'Recognizing receipts and business cards', and dreamed of follow-up courses such as 'Machine Learning, Deep Learning Computer Vision Comprehensive Course', 'Mobile Deep Learning Computer Vision Practical Project', and 'Robot IoT Deep Learning Practical Project'.

 

As a bonus, you will learn about Raspberry Pi in the lecture 'Python Raspberry Pi IoT Project - Remote Monitoring Car'.

In the lecture 'Complete Mastery of Angular Firebase - PetStore Shopping Mall Project', lectures on Firebase are provided in a special lecture format.

 

🌈 Project Introduction

Let's implement a function to recognize directly written numbers using deep learning technology using a Raspberry Pi, a web camera, and OpenCV.

 

Deep learning can be used to find a variety of objects (Object Recognition). YOLO and friends count the number of parked cars in an image.

Count the numbers and save them to a cloud server in real time.

 

The latest Computer Vision technology recognizes letters and numbers in images and videos (Text Recognition).

Let's do a fun project to recognize a car's license plate using a camera.

 

Now let's identify faces and eyes (Face, Eye Detection) in images and videos and confirm their movements using deep learning.

It checks if you are dozing off with a real-time video and wakes you up with an alarm if you are dozing off.

 

You can create an access control system that not only recognizes faces but also confirms movements.

When a registered person enters, notify me via server, dropbox, or email. When an unregistered person enters, sound an alarm.

 

🙌 What tools do you use?

What tools will be covered in this lecture?

This course is based on OpenCV, a representative ComputerVision software library, Python, and TensorFlow.

And we use Raspberry Pi, a representative of the Internet of Things (IoT).

In addition to this, we will explain how to install some useful software one by one in the lecture.

🙋🏻‍♂️ I'm curious!

Q. What are the features of this course?

A. I thought about how to use deep learning and machine learning in practice.

This course will teach you deep learning through practical projects as well as theoretical explanations related to Computer Vision, a representative field.

In particular, we are helping you create practical projects that can be applied in the field using Raspberry Pi so that you can utilize them in the future.

Q. Can non-majors also take the course?

A. Deep learning and data science are not fields that only those with a computer science major can pursue.

This is something you can learn and use if you have the passion.