Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Omlin, Christian"'
Recent advancements in artificial intelligence promise ample potential in monitoring applications with surveillance cameras. However, concerns about privacy and model bias have made it challenging to utilize them in public. Although de-identification
Externí odkaz:
http://arxiv.org/abs/2410.18717
Autor:
Asres, Mulugeta Weldezgina, Omlin, Christian Walter, Wang, Long, Parygin, Pavel, Yu, David, Dittmann, Jay, Collaboration, The CMS-HCAL
The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains for various purposes, including monitoring, diagnostics, and prognostics applications. Data curation is a time-consuming process for a large volume of
Externí odkaz:
http://arxiv.org/abs/2408.16612
Autor:
Asres, Mulugeta Weldezgina, Omlin, Christian Walter, Dittmann, Jay, Parygin, Pavel, Hiltbrand, Joshua, Cooper, Seth I., Cummings, Grace, Yu, David
Identifying outlier behavior among sensors and subsystems is essential for discovering faults and facilitating diagnostics in large systems. At the same time, exploring large systems with numerous multivariate data sets is challenging. This study pre
Externí odkaz:
http://arxiv.org/abs/2404.08453
Autor:
Asres, Mulugeta Weldezgina, Omlin, Christian Walter, Wang, Long, Yu, David, Parygin, Pavel, Dittmann, Jay, Karapostoli, Georgia, Seidel, Markus, Venditti, Rosamaria, Lambrecht, Luka, Usai, Emanuele, Ahmad, Muhammad, Menendez, Javier Fernandez, Maeshima, Kaori, Collaboration, the CMS-HCAL
The compact muon solenoid (CMS) experiment is a general-purpose detector for high-energy collision at the large hadron collider (LHC) at CERN. It employs an online data quality monitoring (DQM) system to promptly spot and diagnose particle data acqui
Externí odkaz:
http://arxiv.org/abs/2311.04190
Autor:
Franco, Muriel Figueredo, Omlin, Christian, Kamer, Oliver, Scheid, Eder John, Stiller, Burkhard
Cybersecurity planning is challenging for digitized companies that want adequate protection without overspending money. Currently, the lack of investments and perverse economic incentives are the root cause of cyberattacks, which results in several e
Externí odkaz:
http://arxiv.org/abs/2304.07909
Crowd anomaly detection is one of the most popular topics in computer vision in the context of smart cities. A plethora of deep learning methods have been proposed that generally outperform other machine learning solutions. Our review primarily discu
Externí odkaz:
http://arxiv.org/abs/2210.13927
Autor:
Vishwanath, Ajay, Bøhn, Einar Duenger, Granmo, Ole-Christoffer, Maree, Charl, Omlin, Christian
Machine ethics has received increasing attention over the past few years because of the need to ensure safe and reliable artificial intelligence (AI). The two dominantly used theories in machine ethics are deontological and utilitarian ethics. Virtue
Externí odkaz:
http://arxiv.org/abs/2208.14037
Autor:
Maree, Charl, Omlin, Christian W.
The proliferation of artificial intelligence is increasingly dependent on model understanding. Understanding demands both an interpretation - a human reasoning about a model's behavior - and an explanation - a symbolic representation of the functioni
Externí odkaz:
http://arxiv.org/abs/2208.12627
Autor:
Maree, Charl, Omlin, Christian W.
Publikováno v:
IEEE CIFEr (2022)
Stock portfolio optimization is the process of continuous reallocation of funds to a selection of stocks. This is a particularly well-suited problem for reinforcement learning, as daily rewards are compounding and objective functions may include more
Externí odkaz:
http://arxiv.org/abs/2207.02134
Publikováno v:
IEEE SSCI (2020)
The application of AI in finance is increasingly dependent on the principles of responsible AI. These principles - explainability, fairness, privacy, accountability, transparency and soundness form the basis for trust in future AI systems. In this st
Externí odkaz:
http://arxiv.org/abs/2206.02419