Posts by Collection




Robust Estimation


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


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


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


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


During the talk, I explained the main idea in certification of machine learning models (either classiffiers or regression models) against adversarial attacks on their inputs, using only a black box access to the model. I showed some synthetic and real world examples of the main theoritical results in the context of autonamous visual positioning systems.