Schönau, Maximilian; Schönau, Elisabeth; Daume, Darwin; Panhuysen, Markus; Schulze, Achim; Hüttl, Bernd; Landes, Dieter (2024)
Schönau, Maximilian; Schönau, Elisabeth; Daume, Darwin; Panhuysen, Markus...
Proceedings of 41th European Photovoltaic Solar Energy Conference and Exhibition.
DOI: 10.4229/EUPVSEC2024/3AV.3.50
Schönau, Maximilian; Daume, Darwin; Panhuysen, Markus; Kreller, Tristan; Jachmann, Joseph; Schulze, Achim; Hüttl, Bernd; Landes, Dieter (2024)
Schönau, Maximilian; Daume, Darwin; Panhuysen, Markus; Kreller, Tristan...
Proceedings of 41th European Photovoltaic Solar Energy Conference and Exhibition.
DOI: 10.4229/EUPVSEC2024/4CV.1.4
Wilde, Mathias; Riedelbauch, Lukas (2024)
Internationales Verkehrswesen 76 (3), 48-50.
Srinivasan, Priya; Tribulowski, Paul; Lindner, Alisa (2024)
Advances in Human Factors of Transportation 2024, 161-171.
DOI: 10.54941/ahfe1005206
Dehghani, Ali; Patiño Studencki, Lucila (2024)
10th. International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS) 2024.
Schaub, Michael (2024)
7. Internationale Fachtagung Bauphysik & Gebäudetechnik (BGT 2024), Friedrichshafen, 365-375.
Och, Hannah; Uddehal, Shabhrish; Strutz, Tilo; Kaup, André (2024)
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'24), 14-19 April 2024, Seoul, South Korea, accepted for publication 2024, 3685 - 3689.
DOI: 10.1109/ICASSP48485.2024.10447125
Screen content images typically contain a mix of natural and synthetic image parts. Synthetic sections usually are comprised of uniformly colored areas and repeating colors and patterns. In the VVC standard, these properties are exploited using Intra Block Copy and Palette Mode. In this paper, we show that pixel-wise lossless coding can outperform lossy VVC coding in such areas. We propose an enhanced VVC coding approach for screen content images using the principle of soft context formation. First, the image is separated into two layers in a block-wise manner using a learning-based method with four block features. Synthetic image parts are coded losslessly using soft context formation, the rest with VVC. We modify the available soft context formation coder to incorporate information gained by the decoded VVC layer for improved coding efficiency. Using this approach, we achieve Bjontegaard-Delta-rate gains of 4.98% on the evaluated data sets compared to VVC.
Och, Hannah; Uddehal, Shabhrish; Strutz, Tilo; Kaup, André (2024)
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'24), 14-19 April 2024, Seoul, South Korea, accepted for publication 2024, 3670 - 3674.
DOI: 10.1109/ICASSP48485.2024.10446445
Soft context formation is a lossless image coding method for screen content. It encodes images pixel by pixel via arithmetic coding by collecting statistics for probability distribution estimation. Its main pipeline includes three stages, namely a context model based stage, a color palette stage and a residual coding stage. Each stage is only employed if the previous stage is impossible since necessary statistics, e.g. colors or contexts, have not been learned yet. We propose the following enhancements: First, information from previous stages is used to remove redundant palette entries and prediction errors in subsequent stages. Additionally, implicitly known stage decision signals are no longer explicitly transmitted. These enhancements lead to an average bit rate decrease of 1.16% on the evaluated data. Compared to FLIF and HEVC, the proposed method needs roughly 0.28 and 0.17 bits per pixel less on average for 24-bit screen content images, respectively.
Schaub, Michael (2024)
Online-Infoveranstaltung der ENERGIEregion Nürnberg e.V..
Schaub, Michael (2024)
Online-Tagung des BTGA „BEG und Großwärmepumpen - Übersicht und aktuelle Informationen“.
DOI: 10.13140/RG.2.2.29962.27847
Schaub, Michael (2024)
Innovation durch Dialog - "Energie intelligent im Unternehmen managen".
Zhou, Lixian; Salaar, Hamza; Schmidt, Michael; Dehghani, Ali; Arbeiter, Georg (2024)
2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI) 2024, 383-390.
DOI: 10.1109/SAMI60510.2024.10432901
Schönau, Maximilian; Daume, Darwin; Panhuysen, Markus; Schulze, Achim; Landes, Dieter (2024)
Schönau, Maximilian; Daume, Darwin; Panhuysen, Markus; Schulze, Achim...
7. Regenerative Energietechnik Konferenz in Nordhausen (RET.Con) 7. RET.Con, 2024 (7), 145-152.
Die präzise Erkennung von Clear-Sky-Momenten ist für die Überwachung und Effizienzana-lyse von Photovoltaikanlagen von zentraler Bedeutung, da zu diesen Zeitpunkten definierte und model-lierbare Einstrahlungsverhältnisse herrschen. Es wird ein hybrides Modell zur verbesserten Erkennung von Clear-Sky-Momenten auf Basis von Einstrahlungsdaten vorgestellt. Hierfür wurden zunächst ma-nuell, dann mithilfe eines CNNs Merkmale aus den Einstrahlungsdaten gebildet. Eine Falls tudie mit Referenzdaten belegt, dass durch die Kombination dieser wissens-und datengetriebenen Methoden Clear-Sky-Momente zuverlässiger identifiziert werden können. Dadurch können Analysemethoden schneller und zuverlässiger Aussagen über die untersuchten PV-Anlagen treffen.
Reißing, Ralf; Bohnen, Katharina; Breithut, Lisa (2024)
Zeitschrift für Verkehrssicherheit (ZVS) 2024 (1), 9-16.
Schaub, Michael (2024)
cci Zeitung 2024 (01), 12-13.
Salaar, Hamza; Dehghani, Ali; Zhou, Lixian; Srinivasan, Priya; Patiño Studencki, Lucila; Arbeiter, Georg; Lindner, Alisa (2023)
Salaar, Hamza; Dehghani, Ali; Zhou, Lixian; Srinivasan, Priya; Patiño Studencki, Lucila...
Tagung Automatisiertes Fahren.
Schaub, Michael (2023)
Vortragsreihe des Klima- und Umweltbeirats der Gemeinde Dörfles-Esbach.
Schaub, Michael (2023)
Themenabend VDI-Bezirksgruppe Coburg.
DOI: 10.13140/RG.2.2.22273.63849
Schaub, Michael (2023)
Transforming Economies.
Schaub, Michael (2023)
Vortragsreihe der Gesundheitstechnischen Gesellschaft (GG) Berlin.
DOI: 10.13140/RG.2.2.30241.17765
Hochschule Coburg
Friedrich-Streib-Str. 2
96450 Coburg