Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Keyhan, Najafian"'
Publikováno v:
Journal of Imaging, Vol 10, Iss 7, p 152 (2024)
Deep learning models have been used for a variety of image processing tasks. However, most of these models are developed through supervised learning approaches, which rely heavily on the availability of large-scale annotated datasets. Developing such
Externí odkaz:
https://doaj.org/article/0184c0866cf34fe38117a33e515fb2a6
Autor:
Keyhan Najafian, Alireza Ghanbari, Mahdi Sabet Kish, Mark Eramian, Gholam Hassan Shirdel, Ian Stavness, Lingling Jin, Farhad Maleki
Publikováno v:
Plant Phenomics, Vol 5 (2023)
Deep learning has shown potential in domains with large-scale annotated datasets. However, manual annotation is expensive, time-consuming, and tedious. Pixel-level annotations are particularly costly for semantic segmentation in images with dense irr
Externí odkaz:
https://doaj.org/article/0770224b2a2b4c0789efa007c34a56cf
Publikováno v:
Bioinformatics Advances. 3
Genomic selection models use Single Nucleotide Polymorphism (SNP) markers to predict phenotypes. However, these predictive models face challenges due to the high dimensionality of genome-wide SNP marker data. Thanks to recent breakthroughs in DNA seq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34aedb8846a48cc0e8fc0ab0937b86b3
https://doi.org/10.1093/bioadv/vbad028
https://doi.org/10.1093/bioadv/vbad028
Autor:
Keyhan Najafian, Alireza Ghanbari, Mahdi Sabet Kish, Mark Eramian, Gholam Hassan Shirdel, Ian Stavness, Lingling Jin, Farhad Maleki
Deep learning has shown potential in domains where large-scale annotated datasets are available. However, manual annotation is expensive, time-consuming, and tedious. Pixel-level annotations are particularly costly for semantic segmentation in images
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02eafd7de149bf407868aceccd794d1f
https://doi.org/10.1101/2022.08.09.503251
https://doi.org/10.1101/2022.08.09.503251
Autor:
Ian Stavness, Keyhan Najafian, Gholam Hassan Shirdel, Lingling Jin, Alireza Ghanbari, Farhad Maleki
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::459bd245ed80daa3865fc4c17059bf24
https://doi.org/10.1109/iccvw54120.2021.00155
https://doi.org/10.1109/iccvw54120.2021.00155
Autor:
Farhad, Maleki, Katie, Ovens, Keyhan, Najafian, Behzad, Forghani, Caroline, Reinhold, Reza, Forghani
Publikováno v:
Neuroimaging clinics of North America. 30(4)
The extensive body of research and advances in machine learning (ML) and the availability of a large volume of patient data make ML a powerful tool for producing models with the potential for widespread deployment in clinical settings. This article p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::e0d9a6aaaa58c7f4c6530659f7a0817d
https://pubmed.ncbi.nlm.nih.gov/33039003
https://pubmed.ncbi.nlm.nih.gov/33039003