Guide-linked quiz · Medium Level
Dilated and Atrous Convolutions Quiz
Check dilation spacing, receptive fields, segmentation, WaveNet, gridding, and parallel multi-scale context in atrous convolutions.
Question 1 of 8
What does a dilation rate greater than 1 do to a convolution kernel?
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Answers and explanations appear as you take the quiz.
- What does a dilation rate greater than 1 do to a convolution kernel?
- It inserts gaps between the kernel weights so they cover a wider area
- It adds more learnable weights to the kernel
- It shrinks the kernel to a single point
- It converts the kernel into a pooling operation
- A 3x3 kernel with a dilation rate of 2 effectively spans how large a region?
- 3x3
- 5x5
- 7x7
- 9x9
- Why are dilated convolutions especially useful for semantic segmentation?
- They reduce the image to a single label
- They eliminate the need for any training data
- They enlarge the receptive field while keeping the feature map resolution high
- They only work on grayscale images
- What does the term atrous originate from?
- A Latin word for layer
- An acronym for a training method
- The name of its inventor
- The French a trous, meaning with holes
- In WaveNet, why are stacked dilated convolutions valuable?
- They generate images instead of audio
- They capture very long-range dependencies in the audio waveform efficiently
- They remove all silence from recordings
- They convert audio into text directly
- What problem can arise if you stack dilated convolutions with a poorly chosen single rate?
- The network becomes too small to train
- The image is permanently rotated
- Gridding artifacts, where some input positions are never sampled
- All weights become zero
- How does Atrous Spatial Pyramid Pooling combine multiple scales in DeepLab?
- It runs several dilation rates in parallel and fuses their outputs
- It chooses one fixed dilation rate and discards the rest
- It converts the image into a single global class before convolution
- It replaces every convolution with a larger dense kernel
- For one input channel and one output channel, how many kernel weights does a dilated 3×3 filter contain, excluding a bias?
- 25, because dilation 2 spans a 5×5 region
- 5, one for each position along the expanded width
- 18, because dilation 2 doubles the number of weights
- 9, because dilation changes spacing rather than the 3×3 weight count
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