Searched for: author%3A%22Neerincx%2C+M.%22
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de Graaf, M.M.A. (author), Perugia, G. (author), Fosch-Villaronga, E. (author), Schaertl Short, E. (author), Lim, A. (author), Broz, F. (author), Neerincx, M. (author)
Discrimination and bias are pressing issues of many AI and robotics applications. These outcomes may derive from limited datasets that do not fully represent society as a whole or from the AI scientific community’s western-male configuration bias. Although being a pressing issue, understanding how robotic systems can replicate and amplify...
conference paper 2022
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Ligthart, M.E.U. (author), Neerincx, M. (author), Hindriks, K.V. (author)
After the novelty effect wears off children need a new motivator to keep interacting with a social robot. Enabling children to build a relationship with the robot is the key for facilitating a sustainable long-term interaction. We designed a memory-based personalization strategy that safeguards the continuity between sessions and tailors the...
conference paper 2022
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Werkhoven, P. (author), Bouwman, J. (author), van Diggelen, J. (author), Dijk, J. (author), van der Meulen, M. (author), Neerincx, M. (author), Raaijmakers, S. (author), van Veenstra, A.F. (author)
TNO has lived up to its motto ‘Innovation for life’ by playing a significant part in this digital revolution, with major breakthroughs in computer simulation, network transactions, wireless communication, cyber security, optical satellite communication and quantum computing.
report 2022
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Huizing, A. (author), Veenman, C.J. (author), Neerincx, M. (author), Dijk, J. (author)
In recent years, AI based on deep learning has achieved tremendous success in specialized tasks such as speech recognition, machine translation, and the detection of tumors in medical images. Despite these successes there are also some clear signs of the limitations of the current state-of-the-art in AI. For example, biases in AI-enabled face...
conference paper 2021
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van Zoelen, E.M. (author), van den Bosch, K. (author), Neerincx, M. (author)
Becoming a well-functioning team requires continuous collaborative learning by all team members. This is called co-learning, conceptualized in this paper as comprising two alternating iterative stages: partners adapting their behavior to the task and to each other (co-adaptation), and partners sustaining successful behavior through communication...
article 2021
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Tajaddini, M. (author), Brinkman, W.P. (author), ten Teije, A. (author), Neerincx, M. (author)
The field of Hybrid Intelligence (HI) is like a vast land with many tribes that speak different languages. Our goal is to develop a linguafranca to unify the peoples of the HI land. We expect our language to facilitate documentation and communication of research results and thus collaboration among various HI fields by making use of design...
conference paper 2021
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van der Waa, J. (author), Nieuwburg, E. (author), Cremers, A. (author), Neerincx, M. (author)
Current developments in Artificial Intelligence (AI) led to a resurgence of Explainable AI (XAI). New methods are being researched to obtain information from AI systems in order to generate explanations for their output. However, there is an overall lack of valid and reliable evaluations of the effects on users' experience of, and behavior in...
article 2021
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van Zoelen, E.M. (author), van den Bosch, K. (author), Rauterberg, M. (author), Barakova, E. (author), Neerincx, M. (author)
As robots become more ubiquitous, they will increasingly need to behave as our team partners and smoothly adapt to the (adaptive) human team behaviors to establish successful patterns of collaboration over time. A substantial amount of adaptations present themselves through subtle and unconscious interactions, which are difficult to observe. Our...
article 2021
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Kraaij, W. (author), Verberne, S. (author), Koldijk, S. (author), de Korte, E. (author), van Dantzig, S. (author), Sappelli, M. (author), Shoaib, M. (author), Bosems, S. (author), Achterkamp, R. (author), Bonomi, A. (author), Schavemaker, J. (author), Hulsebosch, B. (author), Wabeke, T. (author), Vollenbroek-Hutten, M. (author), Neerincx, M. (author), Sinderen, M. (author)
Recent advances in wearable sensor technology and smartphones enable simple and affordable collection of personal analytics. This paper reflects on the lessons learned in the SWELL project that addressed the design of user-centered ICT applications for self-management of vitality in the domain of knowledge workers. These workers often have a...
article 2020
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Waa, J.V.D. (author), Schoonderwoerd, T. (author), Diggelen, J.V. (author), Neerincx, M. (author)
Decision support systems (DSS) have improved significantly but are more complex due to recent advances in Artificial Intelligence. Current XAI methods generate explanations on model behaviour to facilitate a user's understanding, which incites trust in the DSS. However, little focus has been on the development of methods that establish and...
article 2020
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van der Waa, J. (author), Robeer, M. (author), van Diggelen, J. (author), Brinkhuis, M. (author), Neerincx, M. (author)
Recent advances in interpretable Machine Learning (iML) and eXplainable AI (XAI) construct explanations based on the importance of features in classification tasks. However, in a high-dimensional feature space this approach may become unfeasible without restraining the set of important features. We propose to utilize the human tendency to ask...
conference paper 2018
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Werkhoven, P. (author), Kester, L. (author), Neerincx, M. (author)
Recent progress in Artificial Intelligence, sensing and network technology, robotics, and (cloud) computing has enabled the development of intelligent autonomous machine systems. Telling such autonomous systems "what to do" in a responsible way, is a non-trivial task. For intelligent autonomous machines to function in human society and...
conference paper 2018
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van der Waa, J. (author), van Diggelen, J. (author), van den Bosch, K. (author), Neerincx, M. (author)
Machine Learning models become increasingly proficient in complex tasks. However, even for experts in the field, it can be difficult to understand what the model learned. This hampers trust and acceptance, and it obstructs the possibility to correct the model. There is therefore a need for transparency of machine learning models. The development...
conference paper 2018
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Jansen, A. (author), van der Beek, D. (author), Cremers, A. (author), Neerincx, M. (author), van Middelaar, J. (author)
report 2018
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Jansen, A. (author), van der Beek, D. (author), Cremers, A. (author), Neerincx, M. (author), van Middelaar, J. (author)
report 2018
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Jansen, A. (author), van der Beek, D. (author), Cremers, A. (author), Neerincx, M. (author), van Middelaar, J. (author)
Employers will ensure the safety and health of their employees in all work-related matters. Do you have full control over the operation of your cobots and the associated risks to your employees in their workplace? Technological developments in the field of AI-assisted learning will enable organizations in the field of robotics to make great...
report 2018
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van der Waa, J. (author), van Diggelen, J. (author), Neerincx, M. (author), Raaijmakers, S. (author)
End-users of machine learning-based systems benefit from measures that quantify the trustworthiness of the underlying models. Measures like accuracy provide for a general sense of model performance, but offer no detailed information on specific model outputs. Probabilistic outputs, on the other hand, express such details, but they are not...
conference paper 2018
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Parasuraman, R. (author), Caccamo, S. (author), Baberg, F. (author), Ogren, P. (author), Neerincx, M. (author)
A reliable wireless connection between the operator and the teleoperated Unmanned Ground Vehicle (UGV) is critical in many Urban Search and Rescue (USAR) missions. Unfortunately, as was seen in e.g. the Fukushima disaster, the networks available in areas where USAR missions take place are often severely limited in range and coverage. Therefore,...
conference paper 2017
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Kang, N. (author), Brinkman, W.P. (author), Birna Van Riemsdijk, M. (author), Neerincx, M. (author)
Expressive virtual audiences are used in scientific research, psychotherapy, and training. To create an expressive virtual audience, developers need to know how specific audience behaviors are associated with certain characteristics of an audience, such as attitude, and how well people can recognize these characteristics. To examine this, four...
article 2016
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Coninx, A. (author), Baxter, P. (author), Oleari, E. (author), Bellini, S. (author), Bierman, B. (author), Blanson Henkemans, O. (author), Canamero, L. (author), Cosi, P. (author), Enescu, V. (author), Ros Espinoza1, R. (author), Hiolle, A. (author), Humbert, R. (author), Bernd Kiefer, B. (author), Kruijff-Korbayova, I. (author), Looije, R. (author), Mosconi, M. (author), Neerincx, M. (author), Paci, G. (author), Patsis, G. (author), Pozzi, C. (author), Sacchitelli, F. (author), Sahli, H. (author), Sanna, A. (author), Sommavilla, G. (author), Tesser, F. (author), Demiris, Y. (author), Belpaeme, T. (author)
Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of...
article 2015
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