Image as pixels

The video tutorial explains how computers perceive images using numbers, focusing on pixel values and the RGB color model. It describes how images are represented in grayscale and how these representations are prepared for neural network input by flattening. The structure of neural networks, including input, hidden, and output layers, is discussed, highlighting how they interpret image data to identify digits. The tutorial aims to provide a foundational understanding of image processing and neural networks.

What is the smallest element of an image that emits a specific color?

• Bit

• Byte

• Pixel

• Frame

In the RGB color model, what color is produced when all values are set to 0%?

• Black

• Blue

• White

• Red

How many values can each color layer in a pixel have in the RGB model?

• 128

• 512

• 1024

• 256

What is the process of converting a two-dimensional image array into a one-dimensional array called?

• Resizing

• Scaling

• Flattening

• Rotating

In a neural network, what does the output layer represent when processing images of digits?

• The brightness of the image

• The digit the image corresponds to

• The color of the image

• The size of the image