Browsing by Subject "Machine learning"

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  • A Framework for Data Integration and Analysis in Radial-Axial Ring Rolling 
    Fahle, Simon; Kuhlenkötter, Bernd (Hannover : publish-Ing., 2020)
    Data-driven analytical approaches such as machine learning bear great potential for increasing productivity in industrial applications. The primary requirement for using those approaches is data. The challenge is to not ...
  • Accurate and rapid gravitational waveform models for binary black hole coalescences 
    Setyawati, Yoshinta Eka (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2021-09-29)
    The first direct gravitational wave detection by LIGO and Virgo in 2015 marked the beginning of the gravitational wave astronomy era. Gravitational waves are an excellent tool to prove general relativity and unveil compact ...
  • Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021 
    Schüppstuhl, Thorsten; Tracht, Kirsten; Raatz, Annika (Cham : Springer Nature, 2022)
    This Open Access proceedings presents a good overview of the current research landscape of assembly, handling and industrial robotics. The objective of MHI Colloquium is the successful networking at both academic and ...
  • Application of Machine Learning on Transport Spot Rate Prediction in the Recycling Industry 
    Green, Thorben; Rokoss, Alexander; Kramer, Kathrin; Schmidt, Matthias (Hannover : publish-Ing., 2022)
    The transport spot rate in trucking logistics is an important factor for market participants in the recycling industry. Knowledge about the current spot rate is essential for operational decision-making in price negotiations ...
  • Approach to a Decision Support Method for Feature Engineering of a Classification of Hydraulic Directional Control Valve Tests 
    Neunzig, Christian; Fahle, Simon; Schulz, Jürgen; Möller, Matthias; Kuhlenkötter, Bernd (Hannover : publish-Ing., 2022)
    Advancing digitalization and high computing power are drivers for the progressive use of machine learning (ML) methods on manufacturing data. Using ML for predictive quality control of product characteristics contributes ...
  • Augmented Virtuality Data Annotation and Human-in-the-Loop Refinement for RGBD Data in Industrial Bin-Picking Scenarios 
    Blank, Andreas; Baier, Lukas; Zwingel, Maximilian; Franke, Jörg (Hannover : publish-Ing., 2022)
    Beyond conventional automated tasks, autonomous robot capabilities aside to human cognitive skills are gaining importance. This comprises goods commissioning and material supply in intralogistics as well as material feeding ...
  • Automatic refinement of training data for classification of satellite imagery 
    Büschenfeld, Torsten; Ostermann, Jörn (Göttingen : Copernicus GmbH, 2012)
    In this paper, we present a method for automatic refinement of training data. Many classifiers from machine learning used in applications in the remote sensing domain, rely on previously labelled training data. This labelling ...
  • Bias in data-driven artificial intelligence systems—An introductory survey 
    Ntoutsi, Erini; Fafalios, Pavlos; Gadiraju, Ujwal; Iosifidis, Vasileios; Nejdl, Wolfgang; Vidal, Maria-Esther; Ruggieri, Salvatore; Turini, Franco; Papadopoulos, Symeon; Krasanakis, Emmanouil; Kompatsiaris, Ioannis; Kinder-Kurlanda, Katharina; Wagner, Claudia; Karimi, Fariba; Fernandez, Miriam; Alani, Harith; Berendt, Bettina; Kruegel, Tina; Heinze, Christian; Broelemann, Klaus; Kasneci, Gjergji; Tiropanis, Thanassis; Staab, Steffen (Hoboken, NJ : Wiley-Blackwell, 2020)
    Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing ...
  • Boosted unsupervised multi-source selection for domain adaptation 
    Vogt, Karsten; Paul, A.; Ostermann, Jörn; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2017)
    Supervised machine learning needs high quality, densely sampled and labelled training data. Transfer learning (TL) techniques have been devised to reduce this dependency by adapting classifiers trained on different, but ...
  • Building generalization using deep learning 
    Sester, Monika; Feng, Yu; Thiemann, Frank (Göttingen : Copernicus GmbH, 2018)
    Cartographic generalization is a problem, which poses interesting challenges to automation. Whereas plenty of algorithms have been developed for the different sub-problems of generalization (e.g. simplification, displacement, ...
  • Calibrating mini-mental state examination scores to predict misdiagnosed dementia patients 
    Vyas, Akhilesh; Aisopos, Fotis; Vidal, Maria-Esther; Garrard, Peter; Paliouras, George (Basel : MDPI AG, 2021)
    Mini-Mental State Examination (MMSE) is used as a diagnostic test for dementia to screen a patient’s cognitive assessment and disease severity. However, these examinations are often inaccurate and unreliable either due to ...
  • Cross-Company Routing Planning: Determining Value Chains in a Dynamic Production Network Through a Decentralized Approach 
    Markert, Julia; Saubke, Dominik; Krenz, Pascal; Hotz, Lothar (Hannover : publish-Ing., 2022)
    Demand-based, local production will gain relevance in the context of sustainability and circular economy. One way to implement local value creation is through establishing highly dynamic networks that consolidate the ...
  • Deep Reinforcement Learning In Production Planning And Control: A Systematic Literature Review 
    Panzer, Marcel; Bender, Benedict; Gronau, Norbert (Hannover : publish-Ing., 2021)
    Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions ...
  • A Digital Twin for Friction Prediction in Dynamic Rubber Applications with Surface Textures 
    Zambrano, Valentina; Brase, Markus; Hernández-Gascón, Belén; Wangenheim, Matthias; Gracia, Leticia A.; Viejo, Ismael; Izquierdo, Salvador; Valdés, José Ramón (Basel : MDPI, 2021)
    Surface texturing is an effective method to reduce friction without the need to change materials. In this study, surface textures were transferred to rubber samples in the form of dimples, using a novel laser surface ...
  • Disarming visualization-based approaches in malware detection systems 
    Saidia Fascí, Lara; Fisichella, Marco; Lax, Gianluca; Qian, Chenyi (Amsterdam [u.a.] : Elsevier Science, 2022)
    Visualization-based approaches have recently been used in conjunction with signature-based techniques to detect variants of malware files. Indeed, it is sufficient to modify some byte of executable files to modify the ...
  • Do We Really Know The Benefit Of Machine Learning In Production Planning And Control? A Systematic Review Of Industry Case Studies. 
    Kramer, Kathrin Julia; Rokoss, Alexander; Schmidt, Matthias (Hannover : publish-Ing., 2021)
    The field of machine learning (ML) is of specific interest for production companies as it displays a perspective to handle the increased complexity within their production planning and control (PPC) processes in an ...
  • Efficiency of deep neural networks for joint angle modeling in digital gait assessment 
    Conte Alcaraz, Javier; Moghaddamnia, Sanam; Peissig, Jürgen (Heidelberg : Springer, 2021)
    Reliability and user compliance of the applied sensor system are two key issues of digital healthcare and biomedical informatics. For gait assessment applications, accurate joint angle measurements are important. Inertial ...
  • An efficient optimization approach for designing machine learning models based on genetic algorithm 
    Hamdia, Khader M.; Zhuang, Xiaoying; Rabczuk, Timon (London : Springer, 2021)
    Machine learning (ML) methods have shown powerful performance in different application. Nonetheless, designing ML models remains a challenge and requires further research as most procedures adopt a trial and error strategy. ...
  • Explainable Deep Reinforcement Learning for Production Control 
    Theumer, Philipp; Edenhofner, Florian; Zimmermann, Roland; Zipfel, Alexander (Hannover : publish-Ing., 2022)
    Due to the growing number of variants and smaller batch sizes manufacturing companies have to cope with increasing material flow complexity. Thus, increasing the difficulty for production planning and control (PPC) to ...
  • Extended Proceedings 4th Summer School on Video Compression and Processing (SVCP) 2018 
    Golestani, Hossein; Meuel, Holger; Voges, Jan; Laude, Thorsten; Erfurt, Johannes; Lim, Wang; Schwarz, Heiko; Marpe, Detlev; Wiegand, Thomas; Genser, Nils; Seiler, Jürgen; Kaup, André; Munderloh, Marco; Dedjouong, Armel; Bahlau, Sascha; Klemt-Albert, Katharina; Ostermann, Jörn; Samayoa, Yasser; Purushothaman, Suraja Koottachiara Nikarth (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2018-07-18)
    Extended Proceedings 4th Summer School on Video Compression and Processing (SVCP) 2018