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[Mobile] Deep Learning Computer Vision Practical Project

AI Artificial Intelligence, it goes without saying that mobile is the trend. But how do you learn machine learning and deep learning and use them on mobile? Now, let's learn useful mobile Computer Vision projects that are used in daily life.

(4.3) 4 reviews

136 learners

Level Intermediate

Course period Unlimited

  • nomad
IONIC
IONIC
Machine Learning(ML)
Machine Learning(ML)
Deep Learning(DL)
Deep Learning(DL)
OpenCV
OpenCV
Computer Vision(CV)
Computer Vision(CV)
IONIC
IONIC
Machine Learning(ML)
Machine Learning(ML)
Deep Learning(DL)
Deep Learning(DL)
OpenCV
OpenCV
Computer Vision(CV)
Computer Vision(CV)

What you will gain after the course

  • Computer Vision Image, Video Processing

  • Understanding and practicing computer vision dnn(deep learning)

  • Implementing deep learning features in mobile PWA web apps, Android, and iOS devices

  • Object Detection in Images and Videos

  • Object Recognition in Images and Videos

  • Face Recognition in Images and Videos

Project 1. Digit Classifier that recognizes handwritten numbers

This project will cover the fundamentals of computer vision and deep learning by recognizing handwritten text.

Project 2. Object Detection for Counting Parking Lot Vehicles

Object Detection technology counts the number of parked vehicles using parking lot cameras and notifies the cloud server in real time.

Project 3. Gesture Recognition: Determining Rock, Paper, Scissors

Computer Vision's Gesture Recognition technology interprets pre-learned rock, paper, scissors movements.

Project 4. Body Segmentation

When you take a picture of your face and body, deep learning uses Body Segmentation technology to segment the body and separate it from the background.

Project 5. Face Recognition

Would you believe that Computer Vision technology can identify facial contours, identify emotions, and even estimate age and gender?

What tools do you use?

What tools will be covered in this course? This course will create web apps that run on all mobile devices: web, Android, and iOS.

Sometimes we use Android Studio to create Android Native apps and sometimes we use Xcode to create iOS Native apps.

However, we mainly use Ionic+Angular Framework to create hybrid web apps that work on both desktop and mobile.

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




Related lectures

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

[Raspberry Pi]
IoT Deep Learning Computer Vision Practical Project

Create fun and useful projects using the various image and video processing techniques and modules you learned in this course.

bonus!!
Provide additional information on this!

1. As a bonus, in the lecture ‘[Raspberry Pi] IoT Deep Learning Computer Vision Practical Project’, there is content related to Object Detection .
In the lecture 'Complete Mastery of Angular Firebase - PetStore Shopping Mall Project', lectures on Firebase are provided in a special lecture format .

2. 'Model accuracy over 99%'  We also offer a special lecture titled 'Raising the bar'. This lecture is titled ' [ Raspberry Pi ] IoT Deep Learning Computer Vision Practical'.  The project began with a question from students in the MNIST handwriting model: "Why can't the MNIST handwriting model say '7' is '7'?" While the model's accuracy is a factor, as are the program's exception handling and the raw MNIST data, the existing Nueral Network model was too simple for training purposes, so I reconfigured it to increase its accuracy to 99.38%.

3. This special lecture will teach you how to create your desired model using TensorFlow and Keras. Using the same images used for YOLO training, you'll train a model with Keras and use it to identify objects. You'll also learn how to train YOLO and Keras, and compare them.

🙋🏻‍♂️ I'm curious!

Q. What are the features of this course?
A. I thought about how to apply deep learning and machine learning in practice.

This course covers not only the theoretical foundations of Computer Vision, a representative field, but also teaches deep learning through practical projects. Specifically, it helps students create practical projects using mobile devices that can be applied in the field, enabling them to leverage their skills in the future.

Q. Can non-majors also take the course?
A. Deep learning and data science aren't necessarily fields exclusive to those with a computer science degree. If you have the passion, you can learn and apply them.

Recommended for
these people

Who is this course right for?

  • Those who want to use deep learning in practice

  • Anyone who wants to implement deep learning on mobile devices

  • Anyone who wants to learn about image processing using deep learning

  • Anyone preparing a project related to Computer Vision

  • Those who want to learn the latest deep learning image processing techniques

  • Anyone who wants example code to use in their Computer Vision projects

Need to know before starting?

  • Willingness to study hard

  • [OpenCV] Python Deep Learning Image Processing Project - Find Son Heung-min!

  • [Raspberry Pi] IoT Deep Learning Computer Vision Practical Project

  • Angular Firebase Complete Conquest - PetStore Shopping Mall Project

  • Ionic, Ionic 100-minute core lecture

  • [Tensorflow2] Complete conquest of Python deep learning - Latest techniques of GAN, BERT, RNN, CNN

Hello
This is

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Learners

494

Reviews

556

Answers

4.4

Rating

25

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Curriculum

All

66 lectures ∙ (11hr 43min)

Published: 
Last updated: 

Reviews

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4 reviews

4.3

4 reviews

  • shjang9198님의 프로필 이미지
    shjang9198

    Reviews 5

    Average Rating 4.6

    5

    100% enrolled

    • adachoi2814님의 프로필 이미지
      adachoi2814

      Reviews 1

      Average Rating 5.0

      5

      100% enrolled

      great.

      • iambrandonsuh0473님의 프로필 이미지
        iambrandonsuh0473

        Reviews 4

        Average Rating 5.0

        5

        5% enrolled

        This is a great lecture to study the deep learning process through various examples. It was also helpful because it explained in detail the process of implementing it on mobile.

        • nomad
          Instructor

          Thank you. I will make better lectures.

      • little4fiend1372님의 프로필 이미지
        little4fiend1372

        Reviews 1

        Average Rating 2.0

        2

        53% enrolled

        The lecture content is great! However, it is inconvenient that I have to go to another site to sign up and view the lecture materials. And in the middle of the class, a file suddenly appears and it says it was a file that was already made in a Raspberry Pi class that I didn't even take, so the flow of the class is interrupted. The Raspberry Pi class and the deep learning class are separate classes, so I wish the contents of other lectures weren't mentioned at all. As a student, I want to learn entirely according to the lecture flow, but if I go to a special lecture and then go to another site, I lose focus.

        $77.00

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