Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Edge AI for Computer Vision
- Overview of Edge AI and its key advantages.
- Comparative analysis: Cloud AI versus Edge AI.
- Critical challenges in real-time image processing.
Deploying Deep Learning Models on Edge Devices
- Introductory insights into TensorFlow Lite and OpenVINO.
- Strategies for optimizing and quantizing models for edge environments.
- Case study: Executing YOLOv8 on edge hardware.
Hardware Acceleration for Real-Time Inference
- Overview of edge computing hardware, including Jetson, Coral, and FPGAs.
- Leveraging GPU and TPU capabilities for acceleration.
- Methods for benchmarking and performance assessment.
Real-Time Object Detection and Tracking
- Implementing object detection using YOLO models.
- Techniques for tracking moving objects in real-time scenarios.
- Improving detection accuracy through sensor fusion.
Optimization Techniques for Edge AI
- Reducing model footprint via pruning and quantization.
- Methods to minimize latency and power consumption.
- Retraining and fine-tuning Edge AI models.
Integrating Edge AI with IoT Systems
- Deploying AI models on smart cameras and connected IoT devices.
- The role of Edge AI in enabling real-time decision-making.
- Managing communication between edge devices and cloud infrastructure.
Security and Ethical Considerations in Edge AI
- Addressing data privacy concerns in Edge AI applications.
- Safeguarding models against adversarial attacks.
- Ensuring compliance with AI regulations and ethical standards.
Summary and Next Steps
Requirements
- A solid understanding of fundamental computer vision concepts.
- Practical experience with Python and established deep learning frameworks.
- Basic proficiency in edge computing principles and IoT device architectures.
Target Audience
- Computer vision engineers.
- AI developers.
- IoT professionals.
21 Hours
Testimonials (1)
That we can cover advance topic and work with real-life example
