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Mobile Application Development

[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)

[Special Lecture Introduction] We are introducing 'Enhancing Face Recognition'.

Hello, Nomad Creator course students?

Thanks to the funding of Wadi's 'We will make you a machine learning, deep learning, and computer vision expert' that was successfully completed recently,

As the new concept of e-books emerged at Criapple and the contents of the books were organized, I organized supplementary contents that I had been asked about or thought were important from the related lecture contents and created a special lecture on the topic of 'Enhancing Face Recognition'.

Among these, I think the lecture '3 Major Face Detection Techniques' will be helpful to many people, so I have released it on YouTube.

And the remaining special lectures are updated for free in the related lectures, '[OpenCV] Python Deep Learning Image Processing Project - Find Son Heung-min!' and '[Raspberry Pi] IoT Deep Learning Computer Vision Practical Project'.

- OpenCV dnn Face Detection Code Explanation 1

- OpenCV dnn Face Detection Code Explanation 2

- Install Face_Recognition library

I am currently working on a new course called '[OpenCV] Python Deep Learning Image Processing Project 2 - Find Bad Apples!'

After this course is created, if there is any content that would be helpful to students taking other courses, I will select it and update it in the relevant course for free.

In this lecture, in addition to enhancing Face Recognition, we are making it a fun lecture to detect drowsiness using Face Landmark, recognize age and gender using Python deep learning, count people passing by using Object Tracking, and identify defective products by training YOLO with photos of defective apples.

Take care of your health and look forward to the new lecture!

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