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pro vyhledávání: '"P. Lukowicz"'
In the many years since the inception of wearable sensor-based Human Activity Recognition (HAR), a wide variety of methods have been introduced and evaluated for their ability to recognize activities. Substantial gains have been made since the days o
Externí odkaz:
http://arxiv.org/abs/2411.14452
Autor:
Palaiodimopoulos, Nikolaos, Frkatovic, Jasmin, Rey, Vitor Fortes, Tschöpe, Matthias, Suh, Sungho, Lukowicz, Paul, Kiefer-Emmanouilidis, Maximilian
Disordered Quantum many-body Systems (DQS) and Quantum Neural Networks (QNN) have many structural features in common. However, a DQS is essentially an initialized QNN with random weights, often leading to non-random outcomes. In this work, we emphasi
Externí odkaz:
http://arxiv.org/abs/2409.16180
Autor:
Bello, Hymalai, Geißler, Daniel, Ray, Lala, Müller-Divéky, Stefan, Müller, Peter, Kittrell, Shannon, Liu, Mengxi, Zhou, Bo, Lukowicz, Paul
Artificial Intelligence (AI) methods are powerful tools for various domains, including critical fields such as avionics, where certification is required to achieve and maintain an acceptable level of safety. General solutions for safety-critical syst
Externí odkaz:
http://arxiv.org/abs/2409.08666
In the human activity recognition research area, prior studies predominantly concentrate on leveraging advanced algorithms on public datasets to enhance recognition performance, little attention has been paid to executing real-time kitchen activity r
Externí odkaz:
http://arxiv.org/abs/2409.06341
Smaller machine learning models, with less complex architectures and sensor inputs, can benefit wearable sensor-based human activity recognition (HAR) systems in many ways, from complexity and cost to battery life. In the specific case of smart facto
Externí odkaz:
http://arxiv.org/abs/2408.14146
Despite the widespread integration of ambient light sensors (ALS) in smart devices commonly used for screen brightness adaptation, their application in human activity recognition (HAR), primarily through body-worn ALS, is largely unexplored. In this
Externí odkaz:
http://arxiv.org/abs/2408.09527
Large Language Models (LLMs) have made significant advances in natural language processing, but their underlying mechanisms are often misunderstood. Despite exhibiting coherent answers and apparent reasoning behaviors, LLMs rely on statistical patter
Externí odkaz:
http://arxiv.org/abs/2408.01168
Autor:
Krupp, Lars, Bley, Jonas, Gobbi, Isacco, Geng, Alexander, Müller, Sabine, Suh, Sungho, Moghiseh, Ali, Medina, Arcesio Castaneda, Bartsch, Valeria, Widera, Artur, Ott, Herwig, Lukowicz, Paul, Karolus, Jakob, Kiefer-Emmanouilidis, Maximilian
Individual teaching is among the most successful ways to impart knowledge. Yet, this method is not always feasible due to large numbers of students per educator. Quantum computing serves as a prime example facing this issue, due to the hype surroundi
Externí odkaz:
http://arxiv.org/abs/2407.17024
Autor:
Geissler, Daniel, Lukowicz, Paul
Hybrid intelligence aims to enhance decision-making, problem-solving, and overall system performance by combining the strengths of both, human cognitive abilities and artificial intelligence. With the rise of Large Language Models (LLM), progressivel
Externí odkaz:
http://arxiv.org/abs/2407.10580
Autor:
Bley, Jonas, Rexigel, Eva, Arias, Alda, Krupp, Lars, Steinert, Steffen, Longen, Nikolas, Lukowicz, Paul, Küchemann, Stefan, Kuhn, Jochen, Kiefer-Emmanouilidis, Maximilian, Widera, Artur
In the rapidly evolving interdisciplinary field of quantum information science and technology, a big obstacle is the necessity of understanding high-level mathematics to solve complex problems. Visualizations like the (dimensional) circle notation en
Externí odkaz:
http://arxiv.org/abs/2406.16556