Search Results for author: Amirhossein Bayat

Found 8 papers, 2 papers with code

Federated Multi-Mini-Batch: An Efficient Training Approach to Federated Learning in Non-IID Environments

no code implementations13 Nov 2020 Reza Nasirigerdeh, Mohammad Bakhtiari, Reihaneh Torkzadehmahani, Amirhossein Bayat, Markus List, David B. Blumenthal, Jan Baumbach

Federated learning has faced performance and network communication challenges, especially in the environments where the data is not independent and identically distributed (IID) across the clients.

Federated Learning

Robustification of Segmentation Models Against Adversarial Perturbations In Medical Imaging

no code implementations23 Sep 2020 Hanwool Park, Amirhossein Bayat, Mohammad Sabokrou, Jan S. Kirschke, Bjoern H. Menze

This paper presents a novel yet efficient defense framework for segmentation models against adversarial attacks in medical imaging.

Frame

A distance-based loss for smooth and continuous skin layer segmentation in optoacoustic images

no code implementations10 Jul 2020 Stefan Gerl, Johannes C. Paetzold, Hailong He, Ivan Ezhov, Suprosanna Shit, Florian Kofler, Amirhossein Bayat, Giles Tetteh, Vasilis Ntziachristos, Bjoern Menze

Raster-scan optoacoustic mesoscopy (RSOM) is a powerful, non-invasive optical imaging technique for functional, anatomical, and molecular skin and tissue analysis.

Feedback Graph Attention Convolutional Network for Medical Image Enhancement

no code implementations24 Jun 2020 Xiaobin Hu, Yanyang Yan, Wenqi Ren, Hongwei Li, Yu Zhao, Amirhossein Bayat, Bjoern Menze

To well exploit global structural information and texture details, we propose a novel biomedical image enhancement network, named Feedback Graph Attention Convolutional Network (FB-GACN).

Graph Attention Graph Similarity +2

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