cpyh18

This is an all-in-one lecture where you can learn the entire process from the basics of deep learning/TensorFlow/computer vision to practical applications through a practical vehicle license plate recognition project. Through various practical exercises, you can develop practical skills to apply the latest deep learning models to custom datasets.

aischool

All-in-one deep learning image recognition with vehicle license plate recognition project and TensorFlow

AISchool

입문

초급

중급이상

텐서플로

Tensorflow

Deep Learning(DL)

Machine Learning(ML)

합성곱신경망

자연어처리(Natural Language Processing)

Course Introduction

Lecture 1 - ML/DL/TensorFlow/CV Fundamentals - Learn deep learning basics and implement basic models in TensorFlow

Lecture 2 - Learning Image Feature Extraction Methods using CNNs - Let's look at the concept of CNNs and standard CNN models

Lecture 3 - Pre-Trained CNN - Let's look at how to use pre-trained CNNs

Lecture 4 - Learning Time Series Feature Extraction Methods Using RNN - Moving Beyond Image Data to Handle Time Series Data

File Structure for Deep Learning Paper Implementation Project

Lesson 5 - Text Detection - Let's find the location of text within an image & Let's carry out a practical project to find car license plates within an image

Notes for Colab Labs Requiring Long Training

Acquiring basic Python knowledge for practical projects

Lecture 6 - Optical Character Recognition (OCR) [Text Recognition] - Recognize text in images and conduct a practical project on vehicle license plate recognition

Lecture 7 - License Plate Recognition - Let's conduct a practical project on vehicle license plate recognition and explore methods for improving deep learning model performance.

Lecture 8 - Object Detection - Let's solidify the concept of Object Detection and explore the principles of the latest deep learning Object Detection models.

Lecture 9 - Object Detection Practical Project - Let's perform Object Detection on a Custom Dataset using the Latest Deep Learning Model

Image Captioning - Automatically generating image descriptions with AI

Generative Adversarial Networks(GAN) - Let's generate Fake Data using AI

Neural Style Transfer - Overlay a painting image on photos

Semantic Image Segmentation - Let's classify images pixel by pixel

Human Pose Estimation - Let's try to predict human pose

Summary of How to Conduct Deep Learning Practical Projects & How to Use Papers With Code & Introduction to Deep Learning Application Areas Beyond Computer Vision