activity
20182021
most citedTowards disease-aware image editing of chest X-rays

1 citations · 1 across the 1 of their papers we have counts for

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5 papers

eess.IV20211 cited

Towards disease-aware image editing of chest X-rays

Aakash Saboo, Sai Niranjan Ramachandran, Kai Dierkes +1

Disease-aware image editing by means of generative adversarial networks (GANs) constitutes a promising avenue for advancing the use of AI in the healthcare sector. Here, we present…

cs.CV2021

ChaLearn LAP Large Scale Signer Independent Isolated Sign Language Recognition Challenge: Design, Results and Future Research

Ozge Mercanoglu Sincan, Julio C. S. Jacques Junior, Sergio Escalera +1

The performances of Sign Language Recognition (SLR) systems have improved considerably in recent years. However, several open challenges still need to be solved to allow SLR to be…

cs.CV2020

AUTSL: A Large Scale Multi-modal Turkish Sign Language Dataset and Baseline Methods

Ozge Mercanoglu Sincan, Hacer Yalim Keles

Sign language recognition is a challenging problem where signs are identified by simultaneous local and global articulations of multiple sources, i.e. hand shape and orientation, h…

cs.CV2019

Semi-supervised Image Attribute Editing using Generative Adversarial Networks

Yahya Dogan, Hacer Yalim Keles

Image attribute editing is a challenging problem that has been recently studied by many researchers using generative networks. The challenge is in the manipulation of selected attr…

cs.CV2018

Learning Multi-scale Features for Foreground Segmentation

Long Ang Lim, Hacer Yalim Keles

Foreground segmentation algorithms aim segmenting moving objects from the background in a robust way under various challenging scenarios. Encoder-decoder type deep neural networks…