Deep Learning and AI Superhero

Chapter 5 Summary

In Chapter 5, we explored the powerful architecture of Convolutional Neural Networks (CNNs), which have become foundational in the field of computer vision. CNNs are designed to process grid-like data, such as images, while preserving the spatial relationships between pixels, making them ideal for tasks like image classification, object detection, and image segmentation.

We began by understanding the core components of CNNs, including convolutional layers, pooling layers, and fully connected layers. Convolutional layers apply filters (or kernels) to the input image to detect local patterns such as edges and textures, which are then passed through activation functions like ReLU to introduce non-linearity. Pooling layers, such as ...