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Deep Learning · section 12 of 19

Object detection & segmentation

1 interview question on object detection & segmentation, each answered in full. Free to read, no account needed.

What are IoU / Jaccard and Tversky losses?

hard
  • IoU (Jaccard) = |P ∩ G| / |P ∪ G|; loss = 1 - IoU.
  • Similar to Dice but stricter.
  • Tversky loss generalizes: T(P, G) = |P∩G| / (∣PG∣  +  α⋅∣PG∣  +  β⋅∣GP∣)( \mid PG \mid \; + \;{\alpha} \cdot \mid PG \mid \; + \;{\beta} \cdot \mid GP \mid ), where α, β control the penalty on false positives vs false negatives.
  • Handy for skewed segmentation where you want to trade recall vs precision. α=β=0.5 recovers Dice.
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