We are happy to announce the last PyData Yerevan December meetup of 2023!
Vahan Huroyan, a Machine Learning Researcher at the YerevaNN research lab, will feature a talk on “Recent Developments in Self-Supervised Learning for Computer Vision.”
During the talk, he will provide an overview of the latest developments in self-supervised learning (SSL) for computer vision. He will delve into its challenges, and discuss future directions for this field.
Self-supervised learning (SSL) is a powerful tool for training computer vision models without the need for extensive labeled data. SSL methods are designed around pretext tasks that force models to learn valuable representations from the training data. These learned representations can then be transferred to downstream tasks, such as:
The two main approaches of SSL include Contrastive learning and Masked image modeling:
Contrastive learning is a general SSL framework that trains models to distinguish between positive and negative pairs of images.
Masked image modeling is a specific type of SSL that involves masking random patches of an image and training the model to predict the masked pixels.
Register now and save the date to join us on December 14, at 19:00, in the 314w, PAB room at AUA to discover more: https://forms.gle/9y2Latee1zmTtGaAA
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