CRITICAL ANALYSIS OF SELF-SUPERVISION: Difference between revisions

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== Introduction ==
== Introduction ==
This paper aims to learn the deep features of CNNs without manual labels by using supervision techniques.
The main idea of  self-supervision approaches is to learn from unlabeled data and pre-train networks via pretext tasks that can be automatically generated from the data itself.


== Previous Work ==
== Previous Work ==

Revision as of 01:36, 25 November 2020

Presented by

Maral Rasoolijaberi

Introduction

Previous Work

Motivation

results

Conclusion

Critiques

References

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