ann map
Predicts HumanVisualSelectivity
The 1For our experiments we are counting the number of AMTHuman Intelligence Tasks (HITs) that were completed. Wedid not exclude AMT workers from completing multiple HITs. The authors posit that this noisiness is because the gradient may fluctuate sharply at small scales, which seems plausible especially given that, duetoReLUactivationfunctions, theoutput generally isnotevencontinuously differentiable. ThisCAM indicates the discriminative regions of the image used by the CNN to identify that class. We used each of the above passive attention methods to acquire attention maps from each of the modelsinthetoppartofTable2.
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