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Course Level Date Clip# Line Interlocutor Content
Oral Assessments Graduate 2024-07-18 3 152 S01 which we normally we are use that so (1.0)
Oral Assessments Graduate 2024-07-18 3 153 S01 we have this one and uh for this image denoising→
Oral Assessments Graduate 2024-07-18 3 154 S01 (1.4) denoising (1.5) we will get uh (1.6) uh x
Oral Assessments Graduate 2024-07-18 3 155 S01 uh explanation of it↘ so that's the whole process
Oral Assessments Graduate 2024-07-18 3 156 UNK %err:PRO
Oral Assessments Graduate 2024-07-18 3 157 S01 of image denoising and which is (0.4) uh we are::
Oral Assessments Graduate 2024-07-18 3 158 S01 how to do for this uh task↘ (0.6)
Oral Assessments Graduate 2024-07-18 3 159 T01 um (0.7) c- can you- what do- what exactly is that-
Oral Assessments Graduate 2024-07-18 3 160 T01 that last variable you put down that x with
Oral Assessments Graduate 2024-07-18 3 161 T01 the line over it↗
Oral Assessments Graduate 2024-07-18 3 162 S01 (0.6) uh actually eh this eh so your question is
Oral Assessments Graduate 2024-07-18 3 163 S01 you are not clear what is it↗
Oral Assessments Graduate 2024-07-18 3 164 T01 yeah
Oral Assessments Graduate 2024-07-18 3 165 S01 (0.3) uh actually uh this uh this means the average
Oral Assessments Graduate 2024-07-18 3 166 S01 uh average uh es- estimation of x
Oral Assessments Graduate 2024-07-18 3 167 S01 so just I mentioned there are a lots of kinds of noise
Oral Assessments Graduate 2024-07-18 3 168 S01 so maybe suppose uh normally when I do the-
Oral Assessments Graduate 2024-07-18 3 169 S01 when we do the image denoising→ this kind of noise
Oral Assessments Graduate 2024-07-18 3 170 S01 are totally different↗ and uh so- so this way it
Oral Assessments Graduate 2024-07-18 3 171 S01 become a more complex problem that maybe uh a-
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