2012–Present: Deep learning revolutionized image recognition performance.
Slide4: How Computer Vision Works
1. Image Acquisition – Capturing images using cameras or sensors.
2. Preprocessing – Enhancing image quality and removing noise.
3. Feature Extraction – Identifying important patterns and shapes.
4. Recognition & Decision – Classifying objects and generating outputs.
Slide5: Key Technologies Behind Computer Vision
Machine Learning – Systems learn patterns from data.
Deep Learning – Multi-layer neural networks improve accuracy.
Convolutional Neural Networks (CNNs) – Specialized for image analysis.
Image Processing – Enhancing and transforming images for analysis.
Slide6: Applications in Healthcare
Detecting diseases from X-rays and MRI scans.
Early cancer and tumor detection.
Automated medical image analysis.
Supports doctors with faster and more accurate decisions.
Slide7: Applications in Security
Face recognition systems for identity verification.
Biometric authentication in smartphones and airports.
Smart surveillance and anomaly detection.
Real-time monitoring for improved public safety.
Slide8: Self-Driving Cars
Detects pedestrians and vehicles in real time.
Recognizes traffic signs and signals.
Identifies road lanes and obstacles.
Enables safe and autonomous navigation decisions.
Slide9: Industrial and Business Applications
Automated inspection in manufacturing.
Product defect detection.
Inventory and object tracking.
Retail analytics and customer behavior insights.
Slide10: Advantages of Computer Vision
High accuracy in image-based tasks.
Processes large volumes of data quickly.
Reduces human error and operational costs.
Operates continuously without fatigue.
Slide11: Challenges and Limitations
Privacy and ethical concerns.
High computational and development costs.
Requires large, high-quality datasets.
Performance can drop in poor lighting or complex environments.
Slide12: Future of Computer Vision
Smarter robots and intelligent assistants.
Advanced healthcare diagnostics.
Fully autonomous transportation systems.
Integration with Augmented Reality and Smart Cities.
Slide13: Conclusion
Computer Vision enables machines to see, analyze, and understand visual information.
It is transforming healthcare, security, transportation, and industry.
Powered by AI and deep learning technologies.
Its impact will continue to grow in the coming years.
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