Search Results for author: Abanoub Ghobrial

Found 4 papers, 2 papers with code

On Self-Supervised Dynamic Incremental Regularised Adaptation

no code implementations13 Nov 2023 Abanoub Ghobrial, Kerstin Eder

In this paper, we give an overview of a recently developed method for dynamic domain adaptation, named DIRA, which relies on a few samples in addition to a regularisation approach, named elastic weight consolidation, to achieve state-of-the-art (SOTA) domain adaptation results.

Domain Adaptation

Evaluation Metrics for DNNs Compression

no code implementations18 May 2023 Abanoub Ghobrial, Samuel Budgett, Dieter Balemans, Hamid Asgari, Phil Reiter, Kerstin Eder

There is a lot of ongoing research effort into developing different techniques for neural networks compression.

Neural Network Compression Object +2

A Trustworthiness Score to Evaluate DNN Predictions

1 code implementation21 Jan 2023 Abanoub Ghobrial, Darryl Hond, Hamid Asgari, Kerstin Eder

Due to the black box nature of deep neural networks (DNN), the continuous validation of DNN during operation is challenging with the absence of a human monitor.

DIRA: Dynamic Domain Incremental Regularised Adaptation

1 code implementation30 Apr 2022 Abanoub Ghobrial, Xuan Zheng, Darryl Hond, Hamid Asgari, Kerstin Eder

We show that DIRA improves on the problem of forgetting and achieves strong gains in performance when retraining using a few samples from the target domain.

Domain Adaptation Image Classification

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