Class 10 AI Made Easy | Unit 5 Computer Vision explained in simple words | CBSE 2026

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🧠 UNIT 5 – Computer Vision | Class 10 AI (417)

🎯 Learning Goals:
Understand Computer Vision, image representation, feature extraction, object detection, segmentation, and Convolutional Neural Networks (CNNs) through theory + hands-on activities.
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📘 Theory Overview
• Introduction to Computer Vision — concept & real-world applications.
• CV Concepts: pixels, resolution, grayscale vs RGB, and common CV tasks.
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🔬 Image Features & Convolution
• Apply the Convolution Operator to process images and extract features.
• Visualize kernel operations and filters.
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🤖 Convolutional Neural Networks (CNN)
• Learn CNN architecture — kernels, layers, and feature maps.
• Activity: Test a basic CNN for image recognition.
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📌 *Aligned with CBSE AI (417) Learning Outcomes | Board Exam 2025 Ready8

📘 What We Cover
• Artificial Intelligence (417) — from basics to projects
• Information Technology (402) & Informatics Practices (065)
• Computer Science & Computer Applications

🧠 Teaching Approach
Concept-first explanations → Visual demonstrations → Practice & Board-level revision
Each chapter follows CBSE learning outcomes with one-shot videos, PYQs, and quick recaps.