YOLOv8 Performance Improvement Masterclass

YOLOv8 Performance Improvement Masterclass, available at $19.99, has an average rating of 4.43, with 38 lectures, based on 86 reviews, and has 503 subscribers.

You will learn about Modify YOLOv8 Architecture to improve object detection speed and accuracy Boost YOLO v8 Speed in CPU mode with OpenVino and Model Quantization Improve YOLOv8 Speed in GPU mode using TensorRT Optimization Tune Hyperparameter Perform Data Augmentation Techniques That Suit Your Dataset Add data semi-automatically with Pseudo-Labeling Deeply Understand YOLOv8 Architecture Perform YOLOv8 Installation and its dependencies Understand how Convolutional Neural Network works This course is ideal for individuals who are Deep Learning – Computer Vision Professionals interested in BOOSTING YOLOv8 performance or Students who are doing final projects and writing thesis/dissertation or Researchers who are searching new ideas or Deep Learning – Computer Vision Enthusiast It is particularly useful for Deep Learning – Computer Vision Professionals interested in BOOSTING YOLOv8 performance or Students who are doing final projects and writing thesis/dissertation or Researchers who are searching new ideas or Deep Learning – Computer Vision Enthusiast.

Enroll now: YOLOv8 Performance Improvement Masterclass

Summary

Title: YOLOv8 Performance Improvement Masterclass

Price: $19.99

Average Rating: 4.43

Number of Lectures: 38

Number of Published Lectures: 38

Number of Curriculum Items: 38

Number of Published Curriculum Objects: 38

Original Price: Rp249,000

Quality Status: approved

Status: Live

What You Will Learn

Modify YOLOv8 Architecture to improve object detection speed and accuracy
Boost YOLO v8 Speed in CPU mode with OpenVino and Model Quantization
Improve YOLOv8 Speed in GPU mode using TensorRT Optimization
Tune Hyperparameter
Perform Data Augmentation Techniques That Suit Your Dataset
Add data semi-automatically with Pseudo-Labeling
Deeply Understand YOLOv8 Architecture
Perform YOLOv8 Installation and its dependencies
Understand how Convolutional Neural Network works

Who Should Attend

Deep Learning – Computer Vision Professionals interested in BOOSTING YOLOv8 performance
Students who are doing final projects and writing thesis/dissertation
Researchers who are searching new ideas
Deep Learning – Computer Vision Enthusiast

Target Audiences

Deep Learning – Computer Vision Professionals interested in BOOSTING YOLOv8 performance
Students who are doing final projects and writing thesis/dissertation
Researchers who are searching new ideas
Deep Learning – Computer Vision Enthusiast

Welcome to the World’s 1st YOLO Performance Improvement Course.

Unleash the Power of Deep Learning and Elevate Your Computer Vision Skills with the YOLOv8 Performance Improvement Masterclass!

The available courses ONLY teach you how to use YOLO (whatever the version). Yes??

Now, are you ready to take your computer vision expertise to the next level?

Look no further! Join our cutting-edge masterclass designed to sharpen your skills in Deep Learning and Computer Vision, focusing on the state-of-the-art YOLOv8 (You Only Look Once) model. This course will advance you in the field of artificial intelligence regardless of your level of experience or your level of enthusiasm.

Why Choose YOLOv8 Performance Improvement Masterclass

Unleash Speed and Accuracy

Discover how to maximize the performance of your YOLOv8 object detection models. Learn proven techniques to optimize speed and accuracy, making your models lightning-fast without compromising accuracy (or only a tiny drop)

Cutting-Edge Techniques

Explore a comprehensive range of cutting-edge techniques, including TensorRT optimization, OpenVino and Quantization, Architecture Modification, Hyperparameter Tuning, Data Augmentation, and Pseudo Labeling. Master how to construct superior AI systems by using the same technologies as industry experts.

Practical Projects

Implement and experiment with each technique, understand their impact, and harness them for your own AI ventures.

Expert Insights

Benefit from our expertise in both research and industry projects.

Why Attend the Masterclass

Career Advancement: Acquire specialized skills that set you apart in the competitive AI job market, opening doors to lucrative career opportunities.
Finish Study ASAP: Find a compelling cutting-edge technique for your final projects. Finish your study and get your degree ASAP.
Get Published in High Impact Journals: Discover inspiration for novelty or contribution to your research. Get published in your dream journals.
Real-World Impact: Transform theory into practice and create AI systems that revolutionize industries.
Exclusive Community: Join a network of similar-interest professionals and helpful mentors.

Testimonials

This course has been taught as workshops that are enthusiastically attended by industrial professionals, researchers, and students. What do they say? Let’s find out!

“The workshop was conducted well. In my opinion, the materials and instructors are outstanding.” -Aris Setiadi, AI Professional

“The workshop was excellent and highly educational. The information was thorough and useful.” -Fikrul Akbar, Ph.D. Student

“The workshop was fantastic! Preparation for my Ph.D.” -Afdhol Dzikri, Aspiring Ph.D. Student

“The workshop was inspiring. It was taught by experts. Highly recommended for those who want to deepen YOLOv8”-Ryanda Narlan, AI Enthusiast

Join Us in Revolutionizing AI Vision

So, what are you waiting for? Don’t miss your chance to be part of a groundbreaking masterclass that will reshape your AI and Computer Vision journey. Let’s elevate AI vision together! Join the masterclass now!

Disclaimer: Your performance increase may be slightly higher/lower than ours. Don’t worry, it is mostly influenced by the characteristics of the dataset used.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction: mAP Values Format

Chapter 2: YOLOv8 Image Size Hyperparameter

Lecture 1: The Effect of Image Size Hyperparameter on Accuracy

Lecture 2: The Effect of Image Size Hyperparameter on Speed

Chapter 3: YOLOv8 Half Precision

Lecture 1: The Effect of Half Precision on Accuracy

Lecture 2: The Effect of Half Precision on Speed

Chapter 4: TensorRT Optimization (GPU Mode)

Lecture 1: Optimizing YOLOv8 Model with TensorRT

Lecture 2: Performance Comparison of YOLOv8 and TensorRT Model

Chapter 5: OpenVINO Quantization (CPU Mode)

Lecture 1: Optimizing YOLOv8 Model with OpenVINO Quantization

Lecture 2: Performance Comparison of YOLOv8 and OpenVINO Quantization Model

Chapter 6: YOLOv8 Architecture Modifications (up to +21 mAP)

Lecture 1: YOLOv8 Architecture Detailed Explanation

Lecture 2: (Small Objects) Modifying YOLOv8 Architecture for Small Objects Detection

Lecture 3: (Small Objects) Train the Modified Model

Lecture 4: (Small Objects) Performance Comparison of Original and Modified YOLOv8 Model

Lecture 5: (Medium Objects) Modifying YOLOv8 Architecture for Medium Objects Detection

Lecture 6: (Big Objects) Modifying YOLOv8 Architecture for Big Objects Detection (+21 mAP)

Lecture 7: (Big Objects) Train the Modified Model

Lecture 8: (Big Objects) Performance Comparison of Original and Modified YOLOv8 Model

Chapter 7: Hyperparameter Tuning

Lecture 1: Hyperparameter Explanation Part 1

Lecture 2: Hyperparameter Explanation Part 2

Lecture 3: Train the YOLOv8 Model with Default Hyperparameter

Lecture 4: Train the YOLOv8 Model with Tuned Hyperparameter

Chapter 8: Data Augmentation

Lecture 1: Data Augmentation Explanation Part 1

Lecture 2: Data Augmentation Explanation Part 2

Lecture 3: Train the YOLOv8 Model with Default Data Augmentation

Lecture 4: Train the YOLOv8 Model with Recommended Data Augmentation

Chapter 9: The Ultimate Solution: Combination (Speed 4x Faster)

Lecture 1: YOLOv8 Architecture Modification Combined with TensorRT

Chapter 10: Adding More Data Semi-Automatically using Pseudo-Labeling

Lecture 1: Pseudo-Labeling

Lecture 2: Training with a Small Part of Dataset

Lecture 3: Automatic Annotation

Lecture 4: Training with All Data

Chapter 11: BASIC: Understanding Deep Learning

Lecture 1: Understanding Deep Learning

Lecture 2: How Convolutional Neural Networks (CNN) works

Lecture 3: Convolutional Neural Networks Summary

Chapter 12: YOLOv8 Oriented Bounding Boxes

Lecture 1: YOLOv8 Oriented Bounding Boxes

Lecture 2: OBB Annotation using Roboflow

Lecture 3: Train the YOLOv8 OBB Model

Lecture 4: Car Detection

Lecture 5: Accuracy Measurement using Mean Average Precision

Instructors

Dr. Priyanto Hidayatullah (Ph.D in AI)
Ph.D in Artificial Intelligence
Stunning Vision AI Academy
Providing high-quality education in AI and Computer Vision.

Rating Distribution

1 stars: 4 votes
2 stars: 3 votes
3 stars: 11 votes
4 stars: 12 votes
5 stars: 56 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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