
Exploring internal representations of self-supervised networks: few-shot learning abilities and comparison with human semantics and recognition of objects
<a href="https://news.google.com/rss/articles/CBMipwFBVV95cUxPRGRENFk1NmROd3ZMdm1BdHViX1h1b3RqM05RRFNucWM3aS05b3ZUTmdTMGRqRF9RX1Jmd0VUQ1VCcW85VWw0NzMwa09pSldsYnlTXzRORTQzRzBrZ2VvdVhzTGJtNE9kM3Q5NVQwZlZsSHhuM2hTT0xKWGdKWTlwX0ZmSmxQVjRSUGcwSmNfMXNCNk1oU2UzRndRdnFGYnBCTHEzd3djZw?oc=5" target="_blank">Exploring internal representations of self-supervised networks: few-shot learning abilities and comparison with human semantics and recognition of objects</a>&nbsp;&nbsp;<font color="#6f6f6f">Frontiers</font>
