37 citations · 73 across the 14 of their papers we have counts for
6 papers · 1 filter
The role of object-centric representations, guided attention, and external memory on generalizing visual relations
Guillermo Puebla, Jeffrey S. Bowers
Visual reasoning is a long-term goal of vision research. In the last decade, several works have attempted to apply deep neural networks (DNNs) to the task of learning visual relati…
Convolutional Neural Networks Trained to Identify Words Provide a Surprisingly Good Account of Visual Form Priming Effects
Dong Yin, Valerio Biscione, Jeffrey Bowers
A wide variety of orthographic coding schemes and models of visual word identification have been developed to account for masked priming data that provide a measure of orthographic…
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…
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…
Learning Translation Invariance in CNNs
Valerio Biscione, Jeffrey Bowers
When seeing a new object, humans can immediately recognize it across different retinal locations: we say that the internal object representation is invariant to translation. It is…
Are there any 'object detectors' in the hidden layers of CNNs trained to identify objects or scenes?
Ella M. Gale, Nicholas Martin, Ryan Blything +2
Various methods of measuring unit selectivity have been developed with the aim of better understanding how neural networks work. But the different measures provide divergent estima…