01 - CNN Fundamentals: Architecture, Training, Deployment
Complete guide to CNN Fundamentals: Architecture, Training, Deployment: architecture, practical implementation and best practices for developers and technical teams.
Computer vision: CNN, object detection with YOLO, image segmentation, GANs, ViT, medical imaging, autonomous driving, and vision model deployment on edge devices.
This series collects 10 articles (approximately 163 minutes of total reading time), designed for a level Advanced. The main topics covered are Computer Vision, CNN, YOLO, object detection.
Complete guide to CNN Fundamentals: Architecture, Training, Deployment: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to Transfer Learning: Fine-tuning ResNet and Vision Models: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to YOLO26: Real-Time Object Detection: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to Object Detection vs Segmentation: Tasks and Techniques: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to Image Segmentation: Semantic, Instance, Panoptic: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to Image Augmentation: Techniques to Prevent Overfitting: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to Building CV Pipelines: OpenCV Integration with PyTorch: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to Deploying YOLO26 on Edge: Raspberry Pi and Jetson: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to Face Detection and Recognition: MediaPipe and Beyond: architecture, practical implementation and best practices for developers and technical teams.
Complete guide to Anomaly Detection with Computer Vision in Manufacturing: architecture, practical implementation and best practices for developers and technical teams.
Have you read all the articles? Check how much you've learned by taking this series' quizzes.