Apply a convolution with a 3x3 filter kernel to an image with a dimension of 4x6. Only use positions where the filter kernel fits entirely into the image. • What is the output dimension of the resulting image? (a) • How is this output dimension changing with the usage of zero padding? (b)

The output dimension of the resulting image after applying a convolution with a 3x3 filter kernel to an image with dimensions 4x6 is 2x4.

The output dimension of the resulting image is determined by subtracting the filter kernel size (3x3) minus 1 from the original image dimensions. In this case, 4 - (3-1) = 2 and 6 - (3-1) = 4, resulting in an output image dimension of 2x4. When zero padding is used, it means adding additional rows and columns of zeros around the original image before applying the convolution. Zero padding ensures that the output dimension of the resulting image matches the original image size. With zero padding, the resulting image size will remain the same as the original image size.

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