Research output per year
Research output per year
Personal profile
Short presentation
Ashkan Tashk, Ph.D. in Electrical engineering, is a Postdoc researcher at the Food Analytics and Biotechnology (FAB) section, University of Copenhagen (KU), Copenhagen, Denmark. His research interests include applied artificial intelligence and machine learning, data analytics, biomedical image processing, pattern recognition, image classification, and object detection.
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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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.Research output: Contribution to conference › Poster › Research › peer-review
Open AccessFile21 Downloads (Pure) -
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, In: Journal of Real-Time Image Processing. 20, 17 p., 9.Research output: Contribution to journal › Journal article › Research › peer-review
1 Citation (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, In: IEEE Access. 11, p. 50295-50309Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile1 Citation (Scopus)2 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 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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, In: Diagnostics. 12, 12, 23 p., 2952.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile2 Downloads (Pure)