IACM Colloquium
Speaker:
Prof. Nikos Komodakis
Computer Science Dept, University of Crete
Title:
The Self-Supervised Learning Paradigm in Computer Vision
Abstract:
In the evolving landscape of machine learning, self-supervised learning has recently surfaced as a compelling paradigm, challenging the conventional dependence on vast labeled datasets. This presentation aims to provide an introduction into the realm of self-supervised learning within the field of computer vision. To that end, we will trace the evolution of self-supervised learning from the early pioneering approaches that paved the way for its adoption to more recent state-of-the-art techniques. Our focus will be on uncovering the fundamental principles and core ideas that underpin these diverse self-supervised learning methods for visual data.
Short Bio:
Nikos Komodakis holds the position of Assistant Professor at the Computer Science Department, University of Crete. He is also affiliated with the Institute of Applied & Computational Mathematics, FORTH, and is a researcher at the Archimedes Center for Research in Artificial Intelligence. Previously, he served as an Associate Professor at Ecole des Ponts ParisTech and held roles as a research scientist at the French National Centre for Scientific Research (CNRS) and a visiting Professor at Ecole Normale Superieure de Cachan. His research focuses on Computer Vision/Image Analysis, Machine Learning, and Artificial Intelligence.
Furthermore, he contributes as an Editorial Board Member/Associate Editor for journals like Computer Vision and Image Understanding, International Journal of Computer Vision, and Computational Intelligence Journal.
Time, Date & Location:
15:00, March 7, 2024, Fotakis Room
Zoom Info:
https://us06web.zoom.us/j/7761040361?pwd=dEs4TFZxck01Vk5PQWR1TUxKdndwUT09&omn=88177438407
Meeting ID: 776 104 0361
Passcode: 787479
Host:
Yannis Pantazis
Speaker:
Prof. Nikos Komodakis
Computer Science Dept, University of Crete
Title:
The Self-Supervised Learning Paradigm in Computer Vision
Abstract:
In the evolving landscape of machine learning, self-supervised learning has recently surfaced as a compelling paradigm, challenging the conventional dependence on vast labeled datasets. This presentation aims to provide an introduction into the realm of self-supervised learning within the field of computer vision. To that end, we will trace the evolution of self-supervised learning from the early pioneering approaches that paved the way for its adoption to more recent state-of-the-art techniques. Our focus will be on uncovering the fundamental principles and core ideas that underpin these diverse self-supervised learning methods for visual data.
Short Bio:
Nikos Komodakis holds the position of Assistant Professor at the Computer Science Department, University of Crete. He is also affiliated with the Institute of Applied & Computational Mathematics, FORTH, and is a researcher at the Archimedes Center for Research in Artificial Intelligence. Previously, he served as an Associate Professor at Ecole des Ponts ParisTech and held roles as a research scientist at the French National Centre for Scientific Research (CNRS) and a visiting Professor at Ecole Normale Superieure de Cachan. His research focuses on Computer Vision/Image Analysis, Machine Learning, and Artificial Intelligence.
Furthermore, he contributes as an Editorial Board Member/Associate Editor for journals like Computer Vision and Image Understanding, International Journal of Computer Vision, and Computational Intelligence Journal.
Time, Date & Location:
15:00, March 7, 2024, Fotakis Room
Zoom Info:
https://us06web.zoom.us/j/7761040361?pwd=dEs4TFZxck01Vk5PQWR1TUxKdndwUT09&omn=88177438407
Meeting ID: 776 104 0361
Passcode: 787479
Host:
Yannis Pantazis