Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Mertes, Silvan"'
Autor:
Mertes, Silvan, Don, Daksitha Withanage, Grothe, Otto, Kuch, Johanna, Schlagowski, Ruben, André, Elisabeth
Modern TTS systems are capable of creating highly realistic and natural-sounding speech. Despite these developments, the process of customizing TTS voices remains a complex task, mostly requiring the expertise of specialists within the field. One rea
Externí odkaz:
http://arxiv.org/abs/2408.12170
Autor:
Mertes, Silvan, Huber, Tobias, Karle, Christina, Weitz, Katharina, Schlagowski, Ruben, Conati, Cristina, André, Elisabeth
In this paper, we demonstrate the feasibility of alterfactual explanations for black box image classifiers. Traditional explanation mechanisms from the field of Counterfactual Thinking are a widely-used paradigm for Explainable Artificial Intelligenc
Externí odkaz:
http://arxiv.org/abs/2405.05295
In the field of affective computing, where research continually advances at a rapid pace, the demand for user-friendly tools has become increasingly apparent. In this paper, we present the AffectToolbox, a novel software system that aims to support r
Externí odkaz:
http://arxiv.org/abs/2402.15195
Autor:
van Rijn, Pol, Mertes, Silvan, Janowski, Kathrin, Weitz, Katharina, Jacoby, Nori, André, Elisabeth
Speech is a natural interface for humans to interact with robots. Yet, aligning a robot's voice to its appearance is challenging due to the rich vocabulary of both modalities. Previous research has explored a few labels to describe robots and tested
Externí odkaz:
http://arxiv.org/abs/2402.05206
Autor:
Boulogne, Luuk H., Lorenz, Julian, Kienzle, Daniel, Schon, Robin, Ludwig, Katja, Lienhart, Rainer, Jegou, Simon, Li, Guang, Chen, Cong, Wang, Qi, Shi, Derik, Maniparambil, Mayug, Muller, Dominik, Mertes, Silvan, Schroter, Niklas, Hellmann, Fabio, Elia, Miriam, Dirks, Ine, Bossa, Matias Nicolas, Berenguer, Abel Diaz, Mukherjee, Tanmoy, Vandemeulebroucke, Jef, Sahli, Hichem, Deligiannis, Nikos, Gonidakis, Panagiotis, Huynh, Ngoc Dung, Razzak, Imran, Bouadjenek, Reda, Verdicchio, Mario, Borrelli, Pasquale, Aiello, Marco, Meakin, James A., Lemm, Alexander, Russ, Christoph, Ionasec, Razvan, Paragios, Nikos, van Ginneken, Bram, Dubois, Marie-Pierre Revel
Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Public access to the training methodology for these solutions remains abse
Externí odkaz:
http://arxiv.org/abs/2306.10484
Autor:
Müller, Dominik, Schröter, Niklas, Mertes, Silvan, Hellmann, Fabio, Elia, Miriam, Reif, Wolfgang, Bauer, Bernhard, André, Elisabeth, Kramer, Frank
COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times. Especially for capacity planning of intensive care units, predicting the future severity of a COVID-19 pat
Externí odkaz:
http://arxiv.org/abs/2305.08660
Autor:
Hellmann, Fabio, Mertes, Silvan, Benouis, Mohamed, Hustinx, Alexander, Hsieh, Tzung-Chien, Conati, Cristina, Krawitz, Peter, André, Elisabeth
In recent years, the increasing availability of personal data has raised concerns regarding privacy and security. One of the critical processes to address these concerns is data anonymization, which aims to protect individual privacy and prevent the
Externí odkaz:
http://arxiv.org/abs/2305.02143
Autor:
Heimerl, Alexander, Prajod, Pooja, Mertes, Silvan, Baur, Tobias, Kraus, Matthias, Liu, Ailin, Risack, Helen, Rohleder, Nicolas, André, Elisabeth, Becker, Linda
We present a multi-modal stress dataset that uses digital job interviews to induce stress. The dataset provides multi-modal data of 40 participants including audio, video (motion capturing, facial recognition, eye tracking) as well as physiological i
Externí odkaz:
http://arxiv.org/abs/2303.07742
Counterfactual explanations are a common tool to explain artificial intelligence models. For Reinforcement Learning (RL) agents, they answer "Why not?" or "What if?" questions by illustrating what minimal change to a state is needed such that an agen
Externí odkaz:
http://arxiv.org/abs/2302.12689
Autor:
Schlagowski, Ruben, Nazarenko, Dariia, Can, Yekta, Gupta, Kunal, Mertes, Silvan, Billinghurst, Mark, André, Elisabeth
With face-to-face music collaboration being severely limited during the recent pandemic, mixed reality technologies and their potential to provide musicians a feeling of "being there" with their musical partner can offer tremendous opportunities. In
Externí odkaz:
http://arxiv.org/abs/2301.09402