ProfessorsProfessors of Syddansk UniversitetAshkan Tashk

Ashkan Tashk

Syddansk Universitet

H-index: 11

Europe-Denmark

About Ashkan Tashk

Ashkan Tashk, With an exceptional h-index of 11 and a recent h-index of 8 (since 2020), a distinguished researcher at Syddansk Universitet, specializes in the field of Digital image processing, biomedical imagery, Analytical Data Science.

His recent articles reflect a diverse array of research interests and contributions to the field:

Butterfly network: a convolutional neural network with a new architecture for multi-scale semantic segmentation of pedestrians

Modelling of Electronic Health Records for Time-Variant Event Learning Beyond Bio-Markers – a Case Study in Prostate Cancer

Epidemiological description and trajectories of patients with prostate cancer in Denmark: an observational study of 7448 patients

AID-U-Net: An Innovative Deep Convolutional Architecture for Semantic Segmentation of Biomedical Images

A CNN Architecture for Detection and Segmentation of Colorectal Polyps from CCE Images

A New Approach Toward Pedestrian Detection based on A Mixture of Region Proposal and Semantic Segmentation Deep Convolution Neural Networks

A Novel Study of Lichen Planopilaris Among Different Iranian Ethnicities based on Computer-aided Programs

Biomedical study of demographics and clinical features of Lichen Planopilaris among the Iranian population

Ashkan Tashk Information

University	Syddansk Universitet
Position	___
Citations(all)	476
Citations(since 2020)	249
Cited By	335
hIndex(all)	11
hIndex(since 2020)	8
i10Index(all)	18
i10Index(since 2020)	6
Email	Access Email
University Profile Page	Syddansk Universitet
Google Scholar	View Google Scholar Profile

Ashkan Tashk Skills & Research Interests

Digital image processing

biomedical imagery

Analytical Data Science

Top articles of Ashkan Tashk

Title	Journal	Author(s)	Publication Date
Butterfly network: a convolutional neural network with a new architecture for multi-scale semantic segmentation of pedestrians	Journal of real-time image processing	MA Alavianmehr Mohammad Sadegh Helfroush Habibollah Danyali Ashkan Tashk	2023/2
Modelling of Electronic Health Records for Time-Variant Event Learning Beyond Bio-Markers – a Case Study in Prostate Cancer	IEEE Access	Jürgen Herp J-M Braun Manuella L Cantuaria Ashkan Tashk TB Pedersen ...	2023/5/3
Epidemiological description and trajectories of patients with prostate cancer in Denmark: an observational study of 7448 patients	BMC Research Notes	Victoria Blanes-Vidal Ashkan Tashk Manuella Lech Cantuaria Rasmus Søgaard Hansen Charlotte A Poulsen ...	2023/11/16
AID-U-Net: An Innovative Deep Convolutional Architecture for Semantic Segmentation of Biomedical Images	Diagnostics Journal	Tashk Ashkan Herp Jürgen Bjørsum-Meyer Thomas Koulaouzidis Anastasios S. Nadimi Esmaeil	2022/11/25
A CNN Architecture for Detection and Segmentation of Colorectal Polyps from CCE Images		Esmaeil Nadimi Ashkan Tashk Kasim E. Şahin Jürgen Herp	2022
A New Approach Toward Pedestrian Detection based on A Mixture of Region Proposal and Semantic Segmentation Deep Convolution Neural Networks		MA Alavianmehr MS Helfroush Habibollah Danyali Ashkan Tashk	2020
A Novel Study of Lichen Planopilaris Among Different Iranian Ethnicities based on Computer-aided Programs	International Journal of Computer Science and Information Technology (IJCSIT)	Maryamsadat Nejadghaderi Ashkan Tashk Parvin Mansouri Zahra Safaei Naraghi	2020
Biomedical study of demographics and clinical features of Lichen Planopilaris among the Iranian population		Maryamsadat Nejadghaderi Ashkan Tashk Parvin Mansouri Zahra Naraghi	2020
An innovative polyp detection method from colon capsule endoscopy images based on a novel combination of RCNN and DRLSE		Ashkan Tashk Esmaeil Nadimi	2020/7/19