Computer Vision
Master visual AI. Learn image processing, object detection, segmentation, and state-of-the-art vision models.
Prerequisites
Complete Level 3: NLP
🎯What You'll Learn
- ✓Image preprocessing and feature extraction
- ✓Object detection with YOLO and R-CNN
- ✓Image segmentation techniques
- ✓Generative adversarial networks for images
- ✓Vision transformers and modern architectures
💪Skills You'll Gain
🏆Learning Outcomes
📖Interactive Modules (10)
Image Preprocessing Pipeline
Master image preprocessing: resizing, normalization, color space conversion for computer vision.
Edge Detection & Filters
Explore edge detection algorithms, filters, and how computers identify object boundaries.
Feature Extraction Demo
Learn feature extraction techniques to identify important patterns in images automatically.
Semantic Segmentation
Understand pixel-level classification, segmenting images into meaningful regions.
Instance Segmentation
Learn to detect and segment individual object instances in complex scenes.
Face Recognition Pipeline
Build face recognition systems using deep learning for identification and verification.
Pose Estimation Simulator
Detect human body keypoints and estimate poses for motion analysis and applications.
Style Transfer Playground
Apply artistic styles to images using neural style transfer and deep learning.
GANs Introduction
Introduction to Generative Adversarial Networks that create realistic synthetic images.
Image Generation with Diffusion
Understand diffusion models like Stable Diffusion for high-quality image generation.