Search Results for author:
Found 4 papers, 0 papers with code
Contrastive Learning Through Time
We propose a family of CLTT algorithms based on state-of-the-art contrastive learning methods and test them on three data sets.
Recurrent Feedback Improves Recognition of Partially Occluded Objects
Recurrent connectivity in the visual cortex is believed to aid object recognition for challenging conditions such as occlusion.
Recurrent Connectivity Aids Recognition of Partly Occluded Objects
Overall, our results suggest that both artificial and biological neural networks can exploit recurrence for improved object recognition.
Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders
Recurrent connections in the visual cortex are thought to aid object recognition when part of the stimulus is occluded.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
