Get to know Undersampled better with 2 real example sentences, the meaning.
Undersampled meaning
Not adequately sampled or surveyed.
Using Undersampled
- The main meaning on this page is: Not adequately sampled or surveyed.
Context around Undersampled
- Average sentence length in these examples: 30.5 words
- Position in the sentence: 0 start, 1 middle, 1 end
- Sentence types: 2 statements, 0 questions, 0 exclamations
Corpus analysis for Undersampled
- In this selection, "undersampled" usually appears in the middle of the sentence. The average example has 30.5 words, and this corpus slice is mostly made up of statements.
- Around the word, data stand out and add context to how "undersampled" is used.
- Recognizable usage signals include compensate for undersampled data maintaining and could be undersampled. That gives this page its own corpus information beyond isolated example sentences.
- By corpus frequency, "undersampled" sits close to words such as aabc, aacr and aacsb, which helps place it inside the broader word index.
Example types with undersampled
The same corpus examples are grouped by length and sentence type, making it easier to see the contexts in which the word appears:
Innovations like single-shot Fourier ptychographic microscopy and the Recurrent-MZ volumetric imaging framework exemplify how deep learning can compensate for undersampled data, maintaining high imaging quality while minimizing photodamage. (30 words)
These codecs tend not to sample the red, green, and blue channels in different ratios, since there is less perceptual motivation for doing so—just the blue channel could be undersampled. (31 words)
These codecs tend not to sample the red, green, and blue channels in different ratios, since there is less perceptual motivation for doing so—just the blue channel could be undersampled. (31 words)
Innovations like single-shot Fourier ptychographic microscopy and the Recurrent-MZ volumetric imaging framework exemplify how deep learning can compensate for undersampled data, maintaining high imaging quality while minimizing photodamage. (30 words)
Example sentences (2)
Innovations like single-shot Fourier ptychographic microscopy and the Recurrent-MZ volumetric imaging framework exemplify how deep learning can compensate for undersampled data, maintaining high imaging quality while minimizing photodamage.
These codecs tend not to sample the red, green, and blue channels in different ratios, since there is less perceptual motivation for doing so—just the blue channel could be undersampled.