Ashkan Tashk

Fastnet+4535326565
E-mailashkanfood.kudk

Rolighedsvej 26
1958 Frederiksberg C

Kort præsentation

Ashkan Tashk, Ph.D. i elektroteknik, er postdoc-forsker ved sektionen Food Analytics and Biotechnology (FAB), Københavns Universitet (KU), København, Danmark. Hans forskningsinteresser omfatter anvendt kunstig intelligens og maskinlæring, dataanalyse, biomedicinsk billedbehandling, mønstergenkendelse, billedklassificering og objektdetektering.

3 Tidsskriftartikel
1 Konferencebidrag i proceedings
1 Poster

A Novel PLS2-Based Algorithm for Imputing Missing Values in Foodomics/Metabolomics Studies with multiple response variables
Tashk, A., Engelsen, S. B., Khakimov, B., Steenstrup Pedersen, K., Sørensen, K. M. & kwr854, K., 2023.
Publikation: Konferencebidrag › Poster › Forskning › peer review

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Butterfly network: a convolutional neural network with a new architecture for multi-scale semantic segmentation of pedestrians
Alavianmehr, M. A., Helfroush, M. S., Danyali, H. & Tashk, A., 2023, I: Journal of Real-Time Image Processing. 20, 17 s., 9.
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

2 Citationer (Scopus)
Modelling of Electronic Health Records for Time-Variant Event Learning Beyond Bio-Markers – a Case Study in Prostate Cancer
Herp, J., Braun, J-M., Cantuaria, M. L., Tashk, A., Pedersen, T. B., Poulsen, M. H. A., Krogh, M., Nadimi, E. S. & Sheikh, S. P., 2023, I: IEEE Access. 11, s. 50295-50309
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

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1 Citationer (Scopus)

3 Downloads (Pure)
A CNN Architecture for Detection and Segmentation of Colorectal Polyps from CCE Images
Tashk, A., Sahin, K. E., Herp, J. & S. Nadimi, E., 2022, 2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS). IEEE, 6 s.
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

2 Citationer (Scopus)
AID-U-Net: An Innovative Deep Convolutional Architecture for Semantic Segmentation of Biomedical Images
Tashk, A., Herp, J., Bjørsum-Meyer, T., Koulaouzidis, A. & Nadimi, E. S., 2022, I: Diagnostics. 12, 12, 23 s., 2952.
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

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4 Downloads (Pure)

Ashkan Tashk

Personlig profil

Kort præsentation

Samarbejde og topforskningsområder i de sidste fem år

Dyk ned i detaljerne

A Novel PLS2-Based Algorithm for Imputing Missing Values in Foodomics/Metabolomics Studies with multiple response variables

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

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

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

Ashkan Tashk

Personlig profil

Kort præsentation

Samarbejde og topforskningsområder i de sidste fem år

Publikation

A Novel PLS2-Based Algorithm for Imputing Missing Values in Foodomics/Metabolomics Studies with multiple response variables

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

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

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