37 citations · 63 across the 10 of their papers we have counts for
Showing 2021Show all
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cs.CV2021★ 7 cited
Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be
Valerio Biscione, Jeffrey S. Bowers
When seeing a new object, humans can immediately recognize it across different retinal locations: the internal object representation is invariant to translation. It is commonly bel…
cs.CV2021
Learning Online Visual Invariances for Novel Objects via Supervised and Self-Supervised Training
Valerio Biscione, Jeffrey S. Bowers
Humans can identify objects following various spatial transformations such as scale and viewpoint. This extends to novel objects, after a single presentation at a single pose, some…
cs.NE2021★ 2 cited
Generalisation in Neural Networks Does not Require Feature Overlap
Jeff Mitchell, Jeffrey S. Bowers
That shared features between train and test data are required for generalisation in artificial neural networks has been a common assumption of both proponents and critics of these…