Artificial Intelligence: Computer Vision

Study Notes

Computer Vision: a field of study focused on enabling computers to interpret and understand visual information from the world
Involves teaching machines to process and analyze visual data from images and videos

Convolutional Neural Networks (CNNs): used for image classification, object detection, and image segmentation
Object Detection Architectures: YOLO (You Only Look Once), SSD (Single Shot Detector), and Faster R-CNN (Region-based Convolutional Neural Networks)
Image Processing: filtering, transformation, and feature extraction techniques

Data Quality: high-quality, diverse, and well-annotated datasets are essential for training accurate models
Variability: handling variations in lighting, pose, and viewpoint
Occlusion: dealing with objects partially or fully occluded in images
Adversarial Attacks: protecting models from maliciously crafted inputs designed to mislead the system

Self-driving cars using computer vision for lane detection, obstacle detection, and traffic signal recognition
Facial recognition systems for security and authentication
Medical imaging analysis for disease diagnosis and treatment planning
Retail and ecommerce applications for product recognition and recommendation

Computer vision is a field of study focused on enabling computers to interpret and understand visual information from the world
It involves teaching machines to process and analyze visual data from images and videos

Image recognition and classification: identifying objects within images
Object detection and tracking: locating and following objects across images or videos
Image segmentation and annotation: dividing images into regions and labeling them
Facial recognition and biometric analysis: identifying individuals and analyzing their features
Medical imaging analysis and diagnosis: analyzing medical images for diagnosis and treatment planning
Autonomous vehicles and robotics: enabling vehicles and robots to navigate and interact with their environment
Surveillance and security systems: monitoring and analyzing video feeds for security purposes

YOLO (You Only Look Once): a real-time object detection system
SSD (Single Shot Detector): a fast and efficient object detection system
Faster R-CNN (Region-based Convolutional Neural Networks): a highly accurate object detection system

Data Quality: high-quality, diverse, and well-annotated datasets are essential for training accurate models
Variability: handling variations in lighting, pose, and viewpoint
Occlusion: dealing with objects partially or fully occluded in images
Adversarial Attacks: protecting models from maliciously crafted inputs designed to mislead the system

Self-driving cars use computer vision for lane detection, obstacle detection, and traffic signal recognition
Facial recognition systems are used for security and authentication
Medical imaging analysis is used for disease diagnosis and treatment planning
Retail and ecommerce applications use computer vision for product recognition and recommendation