How a CNN sees images simplified 🧠

1. Input → Image breaks into pixels (RGB numbers)

2. Feature Extraction

· Convolution → Detects edges/patterns
· ReLU → Kills negatives, adds non-linearity
· Pooling → Shrinks data, keeps what matters

3. Fully Connected → Flattens features into meaning

4. Output → Probability scores: Cat? Dog? Car?

Why powerful: Learns hierarchically — edges → shapes → objects

Pixels to predictions. That's it. 👇

#DeepLearning #CNN #ComputerVision #AI

https://t.me/CodeProgrammer