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SUMMARY:Discussion
DTSTART;VALUE=DATE-TIME:20260615T090000Z
DTEND;VALUE=DATE-TIME:20260615T093000Z
DTSTAMP;VALUE=DATE-TIME:20260610T161845Z
UID:indico-contribution-494-1998@events.ncbj.gov.pl
DESCRIPTION:https://events.ncbj.gov.pl/event/494/contributions/1998/
LOCATION:Zoom https://cern.zoom.us/j/66151941204?pwd=n7upvvZYibexBhbtyn5kv
 Tpy36L0Wo.1
URL:https://events.ncbj.gov.pl/event/494/contributions/1998/
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SUMMARY:Self-supervised background priors and the inductive erasure of the
  rare class: lessons from a low-surface-brightness detection pipeline (or:
  the model is trying to erase what I'm looking for).
DTSTART;VALUE=DATE-TIME:20260615T080000Z
DTEND;VALUE=DATE-TIME:20260615T090000Z
DTSTAMP;VALUE=DATE-TIME:20260610T161845Z
UID:indico-contribution-494-1997@events.ncbj.gov.pl
DESCRIPTION:Speakers: Krzysztof Nawrocki (NCBJ)\nWe present an in-progress
  open-world detection pipeline for low-surface-brightness sources in multi
 -band astronomical imaging (DES DR1\, 5 bands\, 222 tiles). The architectu
 re composes three stages: a Masked Image Modeling (MIM) self-supervised ba
 ckground prior\; a multi-scale matched-filter detector on the MIM residual
 \, with PSF-convolved Sersic kernels per band and combined-band SNR\; and 
 a hybrid classification head built from a foundation-model embedding\, a M
 amba sequence block\, and engineered shape and color statistics. The pipel
 ine reaches 95–99% recall on existing LSB catalogs and produces a workin
 g pool of novel candidates. Several ML-interesting design tensions emerged
  along the way — trade-offs between background-model expressivity and ra
 re-class preservation\, multi-channel feature integration\, and calibratio
 n under partial ground truth —   which we present in the hope of initiat
 ing discussion.\n\nhttps://events.ncbj.gov.pl/event/494/contributions/1997
 /
LOCATION:Zoom https://cern.zoom.us/j/66151941204?pwd=n7upvvZYibexBhbtyn5kv
 Tpy36L0Wo.1
URL:https://events.ncbj.gov.pl/event/494/contributions/1997/
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