Edge AI for Computer Vision: Real-Time Image Processing Training Course
Edge AI for Computer Vision is revolutionizing real-time image and video analysis by enabling AI models to run directly on edge devices, reducing latency and improving efficiency.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level computer vision engineers, AI developers, and IoT professionals who wish to implement and optimize computer vision models for real-time processing on edge devices.
By the end of this training, participants will be able to:
- Understand the fundamentals of Edge AI and its applications in computer vision.
- Deploy optimized deep learning models on edge devices for real-time image and video analysis.
- Use frameworks like TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
- Optimize AI models for performance, power efficiency, and low-latency inference.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction to Edge AI for Computer Vision
- Overview of Edge AI and its benefits
- Comparison: Cloud AI vs Edge AI
- Key challenges in real-time image processing
Deploying Deep Learning Models on Edge Devices
- Introduction to TensorFlow Lite and OpenVINO
- Optimizing and quantizing models for edge deployment
- Case study: Running YOLOv8 on an edge device
Hardware Acceleration for Real-Time Inference
- Overview of edge computing hardware (Jetson, Coral, FPGAs)
- Leveraging GPU and TPU acceleration
- Benchmarking and performance evaluation
Real-Time Object Detection and Tracking
- Implementing object detection with YOLO models
- Tracking moving objects in real-time
- Enhancing detection accuracy with sensor fusion
Optimization Techniques for Edge AI
- Reducing model size with pruning and quantization
- Techniques for reducing latency and power consumption
- Edge AI model retraining and fine-tuning
Integrating Edge AI with IoT Systems
- Deploying AI models on smart cameras and IoT devices
- Edge AI and real-time decision-making
- Communication between edge devices and cloud systems
Security and Ethical Considerations in Edge AI
- Data privacy concerns in edge AI applications
- Ensuring model security against adversarial attacks
- Compliance with AI regulations and ethical AI principles
Summary and Next Steps
Requirements
- Familiarity with computer vision concepts
- Experience with Python and deep learning frameworks
- Basic knowledge of edge computing and IoT devices
Audience
- Computer vision engineers
- AI developers
- IoT professionals
Need help picking the right course?
macao@nobleprog.com or +852 81990613
Edge AI for Computer Vision: Real-Time Image Processing Training Course - Enquiry
Edge AI for Computer Vision: Real-Time Image Processing - Consultancy Enquiry
Testimonials (1)
That we can cover advance topic and work with real-life example
Ruben Khachaturyan - iris-GmbH infrared & intelligent sensors
Course - Advanced Edge AI Techniques
Related Courses
5G and Edge AI: Enabling Ultra-Low Latency Applications
21 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at intermediate-level telecom professionals, AI engineers, and IoT specialists who wish to explore how 5G networks accelerate Edge AI applications.
By the end of this training, participants will be able to:
- Understand the fundamentals of 5G technology and its impact on Edge AI.
- Deploy AI models optimized for low-latency applications in 5G environments.
- Implement real-time decision-making systems using Edge AI and 5G connectivity.
- Optimize AI workloads for efficient performance on edge devices.
6G and the Intelligent Edge
21 Hours6G and the Intelligent Edge is a forward-looking course that explores the integration of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to support intelligent, low-latency, and adaptive infrastructures.
This instructor-led, live training (online or onsite) is aimed at intermediate-level IT architects who wish to understand and design next-generation distributed architectures leveraging the synergy of 6G connectivity and intelligent edge systems.
Upon completion of this course, participants will be able to:
- Understand how 6G will transform edge computing and IoT architectures.
- Design distributed systems for ultra-low latency, high bandwidth, and autonomous operations.
- Integrate AI and data analytics at the edge for intelligent decision-making.
- Plan scalable, secure, and resilient 6G-ready edge infrastructures.
- Evaluate business and operational models enabled by 6G-edge convergence.
Format of the Course
- Interactive lectures and discussions.
- Case studies and applied architecture design exercises.
- Hands-on simulation with optional edge or container tools.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Advanced Edge AI Techniques
14 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at advanced-level AI practitioners, researchers, and developers who wish to master the latest advancements in Edge AI, optimize their AI models for edge deployment, and explore specialized applications across various industries.
By the end of this training, participants will be able to:
- Explore advanced techniques in Edge AI model development and optimization.
- Implement cutting-edge strategies for deploying AI models on edge devices.
- Utilize specialized tools and frameworks for advanced Edge AI applications.
- Optimize performance and efficiency of Edge AI solutions.
- Explore innovative use cases and emerging trends in Edge AI.
- Address advanced ethical and security considerations in Edge AI deployments.
Building AI Solutions on the Edge
14 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at intermediate-level developers, data scientists, and tech enthusiasts who wish to gain practical skills in deploying AI models on edge devices for various applications.
By the end of this training, participants will be able to:
- Understand the principles of Edge AI and its benefits.
- Set up and configure the edge computing environment.
- Develop, train, and optimize AI models for edge deployment.
- Implement practical AI solutions on edge devices.
- Evaluate and improve the performance of edge-deployed models.
- Address ethical and security considerations in Edge AI applications.
Building Secure and Resilient Edge AI Systems
21 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at advanced-level cybersecurity professionals, AI engineers, and IoT developers who wish to implement robust security measures and resilience strategies for Edge AI systems.
By the end of this training, participants will be able to:
- Understand security risks and vulnerabilities in Edge AI deployments.
- Implement encryption and authentication techniques for data protection.
- Design resilient Edge AI architectures that can withstand cyber threats.
- Apply secure AI model deployment strategies in edge environments.
Cambricon MLU Development with BANGPy and Neuware
21 HoursCambricon MLUs (Machine Learning Units) are specialized AI chips optimized for inference and training in edge and datacenter scenarios.
This instructor-led, live training (online or onsite) is aimed at intermediate-level developers who wish to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.
By the end of this training, participants will be able to:
- Set up and configure the BANGPy and Neuware development environments.
- Develop and optimize Python- and C++-based models for Cambricon MLUs.
- Deploy models to edge and data center devices running Neuware runtime.
- Integrate ML workflows with MLU-specific acceleration features.
Format of the Course
- Interactive lecture and discussion.
- Hands-on use of BANGPy and Neuware for development and deployment.
- Guided exercises focused on optimization, integration, and testing.
Course Customization Options
- To request a customized training for this course based on your Cambricon device model or use case, please contact us to arrange.
CANN for Edge AI Deployment
14 HoursHuawei's Ascend CANN toolkit enables powerful AI inference on edge devices such as the Ascend 310. CANN provides essential tools for compiling, optimizing, and deploying models where compute and memory are constrained.
This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and integrators who wish to deploy and optimize models on Ascend edge devices using the CANN toolchain.
By the end of this training, participants will be able to:
- Prepare and convert AI models for Ascend 310 using CANN tools.
- Build lightweight inference pipelines using MindSpore Lite and AscendCL.
- Optimize model performance for limited compute and memory environments.
- Deploy and monitor AI applications in real-world edge use cases.
Format of the Course
- Interactive lecture and demonstration.
- Hands-on lab work with edge-specific models and scenarios.
- Live deployment examples on virtual or physical edge hardware.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Edge AI for Agriculture: Smart Farming and Precision Monitoring
21 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at beginner-level to intermediate-level agritech professionals, IoT specialists, and AI engineers who wish to develop and deploy Edge AI solutions for smart farming.
By the end of this training, participants will be able to:
- Understand the role of Edge AI in precision agriculture.
- Implement AI-driven crop and livestock monitoring systems.
- Develop automated irrigation and environmental sensing solutions.
- Optimize agricultural efficiency using real-time Edge AI analytics.
Edge AI in Autonomous Systems
14 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who wish to leverage Edge AI for innovative autonomous system solutions.
By the end of this training, participants will be able to:
- Understand the role and benefits of Edge AI in autonomous systems.
- Develop and deploy AI models for real-time processing on edge devices.
- Implement Edge AI solutions in autonomous vehicles, drones, and robotics.
- Design and optimize control systems using Edge AI.
- Address ethical and regulatory considerations in autonomous AI applications.
Edge AI: From Concept to Implementation
14 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI from concept to practical implementation, including setup and deployment.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of Edge AI.
- Set up and configure Edge AI environments.
- Develop, train, and optimize Edge AI models.
- Deploy and manage Edge AI applications.
- Integrate Edge AI with existing systems and workflows.
- Address ethical considerations and best practices in Edge AI implementation.
AI Facial Recognition Development for Law Enforcement
21 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at beginner-level law enforcement personnel who wish to transition from manual facial sketching to using AI tools for developing facial recognition systems.
By the end of this training, participants will be able to:
- Understand the fundamentals of Artificial Intelligence and Machine Learning.
- Learn the basics of digital image processing and its application in facial recognition.
- Develop skills in using AI tools and frameworks to create facial recognition models.
- Gain hands-on experience in creating, training, and testing facial recognition systems.
- Understand ethical considerations and best practices in the use of facial recognition technology.
Fiji: Introduction to Scientific Image Processing
21 HoursFiji is a powerful open-source image processing package that bundles ImageJ (a program designed for scientific multidimensional images) along with a comprehensive suite of plugins for scientific image analysis.
In this instructor-led, live training, participants will learn how to leverage the Fiji distribution and its underlying ImageJ program to create robust image analysis applications.
By the end of this training, participants will be able to:
- Use Fiji's advanced programming features and software components to extend ImageJ capabilities
- Stitch large 3D images from overlapping tiles
- Automate the update of a Fiji installation on startup using the integrated update system
- Select from a broad selection of scripting languages to build custom image analysis solutions
- Utilize Fiji's powerful libraries, such as ImgLib, to process large bioimage datasets efficiently
- Deploy applications and collaborate effectively with other scientists on similar projects
Format of the Course
- Interactive lecture and discussion
- Extensive exercises and practical application
- Hands-on implementation in a live-lab environment
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Fiji: Image Processing for Biotechnology and Toxicology
14 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at beginner-level to intermediate-level researchers and laboratory professionals who wish to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.
By the end of this training, participants will be able to:
- Navigate the Fiji interface and utilize ImageJ’s core functions.
- Preprocess and enhance scientific images for better analysis.
- Analyze images quantitatively, including cell counting and area measurement.
- Automate repetitive tasks using macros and plugins.
- Customize workflows for specific image analysis needs in biological research.
Python and Deep Learning with OpenCV 4
14 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at software engineers who wish to program in Python with OpenCV 4 for deep learning.
By the end of this training, participants will be able to:
- View, load, and classify images and videos using OpenCV 4.
- Implement deep learning in OpenCV 4 with TensorFlow and Keras.
- Run deep learning models and generate impactful reports from images and videos.
Vision Builder for Automated Inspection
35 HoursThis instructor-led, live training in Macao (online or onsite) is aimed at intermediate-level professionals who wish to use Vision Builder AI to design, implement, and optimize automated inspection systems for SMT (Surface-Mount Technology) processes.
By the end of this training, participants will be able to:
- Set up and configure automated inspections using Vision Builder AI.
- Acquire and preprocess high-quality images for analysis.
- Implement logic-based decisions for defect detection and process validation.
- Generate inspection reports and optimize system performance.