Row 12677

Row ID: 12677 | Dataset Entry | Axioma AXP Content Repository

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Most models let you cast your images to floating point allowing you to use whatever precision you want. At this point there would be no loss. However should you for one reason or another chose to normalise to 8 bits: The loss of information is exactly what is written. However if it will impair or even be noticeable is entirely depending on your data. Does tiny differences carry significant information? I would try with and without, intuitively the more precision the better, but sometimes reducing precision can have a denoising effect.

FieldValue
text Most models let you cast your images to floating point allowing you to use whatever precision you want. At this point there would be no loss. However should you for one reason or another chose to normalise to 8 bits: The loss of information is exactly what is written. However if it will impair or even be noticeable is entirely depending on your data. Does tiny differences carry significant information? I would try with and without, intuitively the more precision the better, but sometimes reducin…
label r/deeplearning
dataType comment
communityName r/deeplearning
datetime 2024-05-20
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Raw Record

{
  "text": "Most models let you cast your images to floating point allowing you to use whatever precision you want. At this point there would be no loss. However should you for one reason or another chose to normalise to 8 bits: The loss of information is exactly what is written. However if it will impair or even be noticeable is entirely depending on your data. Does tiny differences carry significant information? I would try with and without, intuitively the more precision the better, but sometimes reducing precision can have a denoising effect.",
  "label": "r/deeplearning",
  "dataType": "comment",
  "communityName": "r/deeplearning",
  "datetime": "2024-05-20",
  "username_encoded": "Z0FBQUFBQm5Lakw2NlVUbFpkN1B3YUFxOEJtNkhiTHh2Z01YTkVLaWFPVmNGSUgzOURiNUs3dDJucGs2S1ZqUmVnRnNtZ0l4bW1wcWdVbzhYbk80MnBJMWFNTFpRNG40VnVlWUtoRi1sbjdEdjE0b2ludmVGbkE9",
  "url_encoded": "Z0FBQUFBQm5Lak9LZTBoYmdEMDVYeXc4LWIzaHl6T092Qzh0MzM0ODA3ek1sNTNCOE1wY0NoV0FnVThUbXVuc0treFQyX1U3VVRQeGNxZWVDeWlSSWY3V3VsWDJPeVNPeE53d0ZvR1hoSHJneFV2WUhib0ZfOE9UVU54Z3VuSVJPeElZcUFDZTQ3bF9xc0dOU3IyekFQMkJVU3c0NWQ5T3JvNFFrSFc4V3Utalotakl1Y2J0OWthaDhRQjNJREdVRFZSWXMza3F0R3ZE"
}
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