Výsledky vyhledávání - "Van Elst, Ludger"

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Generative Language Models Potential for Requirement Engineering Applications: Insights into Current Strengths and Limitations

Autor: Saleem, Summra, Asim, Muhammad Nabeel, Van Elst, Ludger, Dengel, Andreas

Traditional language models have been extensively evaluated for software engineering domain, however the potential of ChatGPT and Gemini have not been fully explored. To fulfill this gap, the paper in hand presents a comprehensive case study to inves

Externí odkaz: http://arxiv.org/abs/2412.00959

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Elektronická kniha

Freiheit : psychobiologische errungenschaft und neurokognitiver auftrag / Ludger Tebartz van Elst. [electronic resource]

Autor: Tebartz van Elst, Ludger, author

Externí odkaz: Kolekce e-knih KNAV Registrovani uzivatele: plny text online 5 minut, dalsi pristup na vyzadani. Registered users: full text online 5 minutes, further access on request.

Elektronická kniha

Epilepsie und Psyche : Psychische Störungen bei Epilepsie - epileptische Phänomene in der Psychiatrie / Ludger Tebartz van Elst, Evgeniy Perlov. [electronic resource]

Autor: Tebartz van Elst, Ludger, author

Externí odkaz: Kolekce e-knih KNAV Registrovani uzivatele: plny text online 5 minut, dalsi pristup na vyzadani. Registered users: full text online 5 minutes, further access on request.

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Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

Autor: Wörmann, Julian, Bogdoll, Daniel, Brunner, Christian, Bührle, Etienne, Chen, Han, Chuo, Evaristus Fuh, Cvejoski, Kostadin, van Elst, Ludger, Gottschall, Philip, Griesche, Stefan, Hellert, Christian, Hesels, Christian, Houben, Sebastian, Joseph, Tim, Keil, Niklas, Kelsch, Johann, Keser, Mert, Königshof, Hendrik, Kraft, Erwin, Kreuser, Leonie, Krone, Kevin, Latka, Tobias, Mattern, Denny, Matthes, Stefan, Motzkus, Franz, Munir, Mohsin, Nekolla, Moritz, Paschke, Adrian, von Pilchau, Stefan Pilar, Pintz, Maximilian Alexander, Qiu, Tianming, Qureishi, Faraz, Rizvi, Syed Tahseen Raza, Reichardt, Jörg, von Rueden, Laura, Sagel, Alexander, Sasdelli, Diogo, Scholl, Tobias, Schunk, Gerhard, Schwalbe, Gesina, Shen, Hao, Shoeb, Youssef, Stapelbroek, Hendrik, Stehr, Vera, Srinivas, Gurucharan, Tran, Anh Tuan, Vivekanandan, Abhishek, Wang, Ya, Wasserrab, Florian, Werner, Tino, Wirth, Christian, Zwicklbauer, Stefan

The availability of representative datasets is an essential prerequisite for many successful artificial intelligence and machine learning models. However, in real life applications these models often encounter scenarios that are inadequately represen

Externí odkaz: http://arxiv.org/abs/2205.04712

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F2DNet: Fast Focal Detection Network for Pedestrian Detection

Autor: Khan, Abdul Hannan, Munir, Mohsin, van Elst, Ludger, Dengel, Andreas

Two-stage detectors are state-of-the-art in object detection as well as pedestrian detection. However, the current two-stage detectors are inefficient as they do bounding box regression in multiple steps i.e. in region proposal networks and bounding

Externí odkaz: http://arxiv.org/abs/2203.02331

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KENN: Enhancing Deep Neural Networks by Leveraging Knowledge for Time Series Forecasting

Autor: Chattha, Muhammad Ali, van Elst, Ludger, Malik, Muhammad Imran, Dengel, Andreas, Ahmed, Sheraz

End-to-end data-driven machine learning methods often have exuberant requirements in terms of quality and quantity of training data which are often impractical to fulfill in real-world applications. This is specifically true in time series domain whe

Externí odkaz: http://arxiv.org/abs/2202.03903

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