Zobrazeno 1 - 10
of 305
pro vyhledávání: '"Barbara Hammer"'
Autor:
Birte Ehrhardt, Hanna Angstmann, Beate Höschler, Draginja Kovacevic, Barbara Hammer, Thomas Roeder, Klaus F. Rabe, Christina Wagner, Karin Uliczka, Susanne Krauss-Etschmann
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Serine proteases are important regulators of airway epithelial homeostasis. Altered serum or cellular levels of two serpins, Scca1 and Spink5, have been described for airway diseases but their function beyond antiproteolytic activity is insu
Externí odkaz:
https://doaj.org/article/6db17430acc04ff2b78194f3ababa535
Publikováno v:
PeerJ Computer Science, Vol 10, p e2317 (2024)
Especially if artificial intelligence (AI)-supported decisions affect the society, the fairness of such AI-based methodologies constitutes an important area of research. In this contribution, we investigate the applications of AI to the socioeconomic
Externí odkaz:
https://doaj.org/article/494edb2943cd4ee39538771ded89b5a8
Autor:
Zafran Hussain Shah, Marcel Müller, Wolfgang Hübner, Henning Ortkrass, Barbara Hammer, Thomas Huser, Wolfram Schenck
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
Real-valued convolutional neural networks (RV-CNNs) in the spatial domain have outperformed classical approaches in many image restoration tasks such as image denoising and super-resolution. Fourier analysis of the results produced by these spatial d
Externí odkaz:
https://doaj.org/article/b82a7cef34744d7ea49c1992fc6ae7c7
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
In an increasing number of industrial and technical processes, machine learning-based systems are being entrusted with supervision tasks. While they have been successfully utilized in many application areas, they frequently are not able to generalize
Externí odkaz:
https://doaj.org/article/208cd65f0611459abe2af379a0b0f580
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
The world surrounding us is subject to constant change. These changes, frequently described as concept drift, influence many industrial and technical processes. As they can lead to malfunctions and other anomalous behavior, which may be safety-critic
Externí odkaz:
https://doaj.org/article/08d5088818ab4d4b917b171c1cca9cc0
Publikováno v:
Applied Artificial Intelligence, Vol 37, Iss 1 (2023)
In many real-world scenarios, data are provided as a potentially infinite stream of samples that are subject to changes in the underlying data distribution, a phenomenon often referred to as concept drift. A specific facet of concept drift is feature
Externí odkaz:
https://doaj.org/article/32738ebc4484455c85f7390faaf97305
Publikováno v:
Frontiers in Computer Science, Vol 5 (2023)
IntroductionTo foster usefulness and accountability of machine learning (ML), it is essential to explain a model's decisions in addition to evaluating its performance. Accordingly, the field of explainable artificial intelligence (XAI) has resurfaced
Externí odkaz:
https://doaj.org/article/99e616ee937a4f3d9c1c68a19f439251
Autor:
Dominik Stallmann, Barbara Hammer
Publikováno v:
Algorithms, Vol 16, Iss 4, p 205 (2023)
Novel neural network models that can handle complex tasks with fewer examples than before are being developed for a wide range of applications. In some fields, even the creation of a few labels is a laborious task and impractical, especially for data
Externí odkaz:
https://doaj.org/article/f536869cd834416da88f7db49dfa4408
Publikováno v:
BMC Psychiatry, Vol 20, Iss 1, Pp 1-9 (2020)
Abstract Clozapine remains the only drug treatment likely to benefit patients with treatment resistant schizophrenia. Its use is complicated by an increased risk of neutropenia and so there are stringent monitoring requirements and restrictions in th
Externí odkaz:
https://doaj.org/article/ceb1614eda10450caf1fc2723c6441ec
Publikováno v:
Data Science and Engineering, Vol 5, Iss 2, Pp 126-139 (2020)
Abstract Convolutional neural networks (CNNs) are deep learning frameworks which are well known for their notable performance in classification tasks. Hence, many skeleton-based action recognition and segmentation (SBARS) algorithms benefit from them
Externí odkaz:
https://doaj.org/article/234b7698fedf42479cf90d59962b730e