Zobrazeno 1 - 10
of 149
pro vyhledávání: '"dataset-bias"'
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-26 (2024)
Abstract Background Deep learning-based drug-target affinity (DTA) prediction methods have shown impressive performance, despite a high number of training parameters relative to the available data. Previous studies have highlighted the presence of da
Externí odkaz:
https://doaj.org/article/0ac6b597a86646beac04eec0ea968c8f
Publikováno v:
Data in Brief, Vol 55, Iss , Pp 110598- (2024)
In online food delivery apps, customers write reviews to reflect their experiences. However, certain restaurants use a “review event” strategy to solicit favorable reviews from customers and boost their revenue. Review event is a marketing strate
Externí odkaz:
https://doaj.org/article/f1e027dc69834ee0beade8ca6a2d7a14
Autor:
Konstantin Sharafutdinov, Sebastian Johannes Fritsch, Mina Iravani, Pejman Farhadi Ghalati, Sina Saffaran, Declan G. Bates, Jonathan G. Hardman, Richard Polzin, Hannah Mayer, Gernot Marx, Johannes Bickenbach, Andreas Schuppert
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 611-620 (2024)
Goal: Machine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and their
Externí odkaz:
https://doaj.org/article/44befcf235114feabf6f4ed4938e85a4
Publikováno v:
IEEE Access, Vol 11, Pp 139706-139714 (2023)
The task of Visual Commonsense Generation (VCG) delves into the deeper narrative behind a static image, aiming to comprehend not just its immediate content but also the surrounding context. The VCG model generates three types of captions for each ima
Externí odkaz:
https://doaj.org/article/5b1a3e2a154149aea336a471112bcc05
Publikováno v:
IEEE Access, Vol 11, Pp 29263-29274 (2023)
Traffic accident anticipation is essential for successful autonomous and assistive driving systems. Existing accident anticipation algorithms that mostly rely on visual features of the accident related objects involved provides both high AP (Average
Externí odkaz:
https://doaj.org/article/2ac04c61675f44d8a6255825e38981bf
Akademický článek
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Akademický článek
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Publikováno v:
IEEE Access, Vol 10, Pp 126832-126844 (2022)
The early 21st-century technological advancements tilted the scales towards data-driven learning. Thus, modern machine-learning systems rely heavily on data to learn complex models to efficiently provide relevant predictions. Data-driven learning suf
Externí odkaz:
https://doaj.org/article/bbf428979f014a92ad77d3c88d8a0091
Autor:
Konstantin Sharafutdinov, Jayesh S. Bhat, Sebastian Johannes Fritsch, Kateryna Nikulina, Moein E. Samadi, Richard Polzin, Hannah Mayer, Gernot Marx, Johannes Bickenbach, Andreas Schuppert
Publikováno v:
Frontiers in Big Data, Vol 5 (2022)
Machine learning (ML) models are developed on a learning dataset covering only a small part of the data of interest. If model predictions are accurate for the learning dataset but fail for unseen data then generalization error is considered high. Thi
Externí odkaz:
https://doaj.org/article/4c8c914b67c34e4eba51ceced1d34906
Autor:
Hector Corrales Sanchez, Noelia Hernandez Parra, Ignacio Parra Alonso, Eduardo Nebot, David Fernandez-Llorca
Publikováno v:
IEEE Access, Vol 9, Pp 116338-116355 (2021)
Fine-grained vehicle classification from images, also known as Vehicle Make and Model Recognition (VMMR), has become an important research topic in the last years, with a growing number of scientific contributions in multiple application areas, such
Externí odkaz:
https://doaj.org/article/7b920aa4ee4f4cafb91cb7ca260dd07c