Computer Vision Problems include:
- Image Classication
- Object Detection
- … …
One of the challenges of computer vision problems is that the input can be very big. For example, a 1000 by 1000 image can have $1000 \times 64 \times 3 = 12288$ dimensions because there are three color channels. If the size of hidden layer is 1000, the number of parameters from input layer to hidden layer could be 3 billion. This will cause these problems:
- data size requirements;
- computational requirements;
- memory requirements.
The problems of convolutional operation:
- shrinking output
- throwing away a lot of information from the edges of the image
In order to fix these problems, what we need to do is pad the image.