Explore the Future of Manufacturing with Image Recognition AI Seminar
Discover the Cutting-Edge Seminar on Image Recognition AI for Manufacturing
The AI Technology Engineer Education Institute is set to host an enlightening seminar on September 7, 2026, from 9:30 AM to 4:30 PM. This online session via Zoom will delve into the world of image recognition AI tailored specifically for the manufacturing sector.
Why Image Recognition AI?
In recent times, the manufacturing industry has witnessed a significant increase in the adoption of image recognition AI, aimed at enhancing quality control and streamlining inspection processes. Traditional methods reliant on visual checks and rule-based inspections are increasingly being supplemented or replaced by automated solutions leveraging machine learning and deep learning technologies. However, establishing a high-precision image recognition system on-site requires a comprehensive understanding of several factors, including the design of shooting conditions, camera selection, image processing, preparation of training data, and performance evaluation.
Seminar Overview
Seminar Title: Image Recognition AI Utilization Seminar for Manufacturing
Date: September 7, 2026 (Monday)
Time: 9:30 AM - 4:30 PM
Location: Online via Zoom
Fee: 49,500 yen (tax included) per person (discounts available for multiple attendees)
Instructor: Ryosuke Kasahara (CTO, BrightVox Co., Ltd.)
This seminar aims to provide professionals in the manufacturing industry with a strong foundation in image recognition technology, ensuring participants gain insights from both theoretical and practical perspectives.
Seminar Details
Attendees will explore the basics of image capturing that influence recognition accuracy along with the characteristics of various camera types. Throughout the session, fundamental principles of machine learning and deep learning will be discussed, covering technologies like CNN, YOLO, and Vision Transformer used in image recognition. The hands-on demonstrations using Python on Google Colab will allow participants to run code independently and validate the entire process of image classification post-seminar.
Seminar Program
- - Overview of Image Recognition Technology
- Key technologies supporting image recognition
- - Effective Image Capturing Basics and Considerations
- Choosing among various types of cameras
- Basics of image processing technology
- Coordinated design between optical systems and image processing
- Approaches utilizing polarized cameras in image recognition
- - From Machine Learning Basics to Applications in Image Recognition
- Applying machine learning to image recognition
- Practical flow for developing image recognition AI
- Preparing training data, designing features, selecting methods, and performance evaluation
- Exercises related to classification problems with limited data
- - Foundations of Deep Learning and Its Application to Image Recognition
- Practical learning methods and improvement techniques
- Understanding of CNN structures and applications
- Code explanations for table data classification, image classification, and defect inspection
- Exercises focusing on improving classification accuracy using CNN in image classification
- - Useful Image Recognition Algorithms in Practice
- Image recognition processing based on machine learning techniques like SIFT and HOG
- CNN networks such as AlexNet, VGG, ResNet
- Object detection algorithms like R-CNN and YOLO
- Image generation, transfer learning, and domain adaptation
- Latest technologies like Vision Transformer
- - Learning from Real-world Examples of Image Recognition Applications
- Algorithms for defect inspection in cast parts
- Detection algorithm for road surface freezing
- Algorithms for defect inspection utilizing transfer learning
- - Latest Trends in Image Recognition Technology and Machine Learning
- Accelerated examples of AI implementation in the manufacturing sector
- Future prospects for next-generation AI technologies
- Applications of Large Language Models (LLM) in image recognition
- Image recognition examples using multimodal large language models
Target Audience
This seminar is designed for engineers and technical personnel involved in implementing or developing image recognition AI and visual inspection systems within the manufacturing industry. It is also ideal for those considering the automation of quality control and inspection processes using image recognition technology. Additionally, it caters to manufacturing professionals, researchers, and practitioners looking to systematically learn the fundamentals of machine learning and deep learning. It is especially beneficial for personnel facing challenges in enhancing the accuracy of their image recognition systems.
For more information about this seminar, please visit AI Technology Engineer Education Institute's Seminar Page.
The AI Technology Engineer Education Institute continues to provide valuable knowledge and practical skills through seminars, e-learning, training, and publication services tailored for technical personnel in the manufacturing sector. The Japan AI Corporation has over 50 years of experience, offering a wide range of specialized services in patent and intellectual property solutions, technology research and analysis, technical education for manufacturing professionals, and the creation of technology-related content.
Contact: 101-0033 Tokyo, Chiyoda-ku, Kanda Iwamotocho 15-1 CYK Kanda Iwamotocho 3rd Floor, TEL: 03-6206-4966
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