CNN_Presentation diving further into the world of neural networks

CNN_Presentation diving further into the world of neural networks

1. Understanding Convolutional Neural Networks (CNNs) A Fun & Interactive Guide

2. What is a Convolutional Neural Network (CNN)? - A special type of AI model used for image recognition - Inspired by the human brain’s vision system - Helps identify objects, faces, animals, and more!

3. Can You Guess This Flower? 🌹 - Imagine seeing a flower image - How do we recognize it as a rose? - What makes it different from a sunflower?

4. How Do We Recognize Objects? - We look for features: color, shape, texture - CNNs also extract features step by step - Example: Rose petals are curved and red

5. Key Components of a CNN - Convolution: Extracts features - Pooling: Reduces size while keeping important info - Fully Connected Layers: Makes predictions - Activation Functions: Adds non-linearity

6. How CNN Recognizes a Rose? 🌹 1. Takes the image of a flower 2. Extracts edges, colors, and textures 3. Detects petal shapes and patterns 4. Compares with learned features 5. Predicts the probability of it being a rose

7. Convolution: Extracting Features - Applies filters to detect patterns (e.g., edges, textures) - Each filter captures different details - Helps break down the image into key elements

8. Pooling: Making it Simpler - Reduces image size while keeping key features - Max pooling picks the most important details - Makes computation faster & avoids overfitting

9. Final Prediction: Is it a Rose? - After feature extraction & pooling - Fully connected layers analyze the data - Softmax predicts probabilities (e.g., 90% rose, 8% sunflower, 2% tulip)

10. CNNs in the Real World 🌎 - Face recognition (e.g., unlocking phones) - Self-driving cars (detecting objects) - Medical imaging (identifying diseases) - Sports analytics (tracking player movements)

11. CNNs Be Like... 🤖 When you teach a CNN to recognize cats, but it starts classifying dogs as cats... 🐱🐶

12. Quick Quiz! 🧠 1. What does convolution do in CNNs? 2. Why do we use pooling? 3. Name a real-world application of CNNs.

13. Thank You! Hope you enjoyed learning about CNNs! 🚀