Associative Based Similarity Search for Few Shot Training


Conventional CNN requires a finite number of pre-known classes with many examples. We present here an associative computing approach and chip architecture for Few Shot training networks using O (1) similarity search and Top K computing. This approach enables only few examples per label, extreme classification and fast adjustment.


Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google