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talks

Robust Estimation

Published:

In this talk, I discussed the challenges of maximum likelihood-based estimators in facing contaminations and outliers. Several metrics were introduced for performance evaluation of a robust estimation method and finally, the well-known robust estimators such as the Huber estimator, Hample estimator, etc. were analyzed with respect to these metrics.

Robust Adaptive Matched Filter

Published:

In this talk, we present an extension of classical adaptive mathched filter for the cases where the secondary set of data is not target-free and the covariance should be estimated differently to not include target signals. (video)

Robust Likelihood Ratio Test

Published:

In this talk, we present an extension of generalized likelihood ratio test for the cases where observes signal is contaimaned with heavy impulsive noise. (video)

Small Object Detection using Deep Learning

Published:

As organizers of this workshop, we discussed challenges in detection and localization of small objects in images and videos. In addition to that, A/Prof. Wanli Ouyang from The University of Sydney and Dr. Emre Akbas from Middle East Technical University (METU) presented their recent research in the field of object detection, with emphasis on small objects. (Link)

Certified Robustness in Machine Learning

Published:

In this talk, I explained the main idea behind the certification techniques in deep learning models (either classiffiers or regression models) against adversarial attacks. I also showed some synthetic and real world examples of the main theoritical results in the context of autonamous visual positioning systems.

Explainable AI

Published:

In this talk, I explained XAI taxonomy and talked about two popular techniques, i.e., Shapley values and Grad-CAM which have been widely used in the literature.

teaching