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| 2. |
- Lu, Zhihan, et al.
(författare)
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Multimodal Hand and Foot Gesture Interaction for Handheld Devices
- 2014
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Ingår i: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP). - : Association for Computing Machinery (ACM). - 1551-6857 .- 1551-6865. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- We present a hand-and-foot-based multimodal interaction approach for handheld devices. Our method combines input modalities (i.e., hand and foot) and provides a coordinated output to both modalities along with audio and video. Human foot gesture is detected and tracked using contour-based template detection (CTD) and Tracking-Learning-Detection (TLD) algorithm. 3D foot pose is estimated from passive homography matrix of the camera. 3D stereoscopic and vibrotactile are used to enhance the immersive feeling. We developed a multimodal football game based on the multimodal approach as a proof-of-concept. We confirm our systems user satisfaction through a user study.
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| 3. |
- Gerken, Jan, 1991, et al.
(författare)
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Equivariance versus augmentation for spherical images
- 2022
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Ingår i: Proceedings of Machine Learning Resaerch. ; , s. 7404-7421
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Konferensbidrag (refereegranskat)abstract
- We analyze the role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images. We compare the performance of the group equivariant networks known as S2CNNs and standard non-equivariant CNNs trained with an increasing amount of data augmentation. The chosen architectures can be considered baseline references for the respective design paradigms. Our models are trained and evaluated on single or multiple items from the MNIST- or FashionMNIST dataset projected onto the sphere. For the task of image classification, which is inherently rotationally invariant, we find that by considerably increasing the amount of data augmentation and the size of the networks, it is possible for the standard CNNs to reach at least the same performance as the equivariant network. In contrast, for the inherently equivariant task of semantic segmentation, the non-equivariant networks are consistently outperformed by the equivariant networks with significantly fewer parameters. We also analyze and compare the inference latency and training times of the different networks, enabling detailed tradeoff considerations between equivariant architectures and data augmentation for practical problems.
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| 4. |
- Lindgren, Helena, Professor, et al.
(författare)
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The wasp-ed AI curriculum : A holistic curriculum for artificial intelligence
- 2023
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Ingår i: INTED2023 Proceedings. - : IATED. - 9788409490264 ; , s. 6496-6502
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Konferensbidrag (refereegranskat)abstract
- Efforts in lifelong learning and competence development in Artificial Intelligence (AI) have been on the rise for several years. These initiatives have mostly been applied to Science, Technology, Engineering and Mathematics (STEM) disciplines. Even though there has been significant development in Digital Humanities to incorporate AI methods and tools in higher education, the potential for such competences in Arts, Humanities and Social Sciences is far from being realised. Furthermore, there is an increasing awareness that the STEM disciplines need to include competences relating to AI in humanity and society. This is especially important considering the widening and deepening of the impact of AI on society at large and individuals. The aim of the presented work is to provide a broad and inclusive AI Curriculum that covers the breadth of the topic as it is seen today, which is significantly different from only a decade ago. It is important to note that with the curriculum we mean an overview of the subject itself, rather than a particular education program. The curriculum is intended to be used as a foundation for educational activities in AI to for example harmonize terminology, compare different programs, and identify educational gaps to be filled. An important aspect of the curriculum is the ethical, legal, and societal aspects of AI and to not limit the curriculum to the STEM subjects, instead extending to a holistic, human-centred AI perspective. The curriculum is developed as part of the national research program WASP-ED, the Wallenberg AI and transformative technologies education development program.
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| 5. |
- Singh, Avinash, 1986-, et al.
(författare)
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Verbal explanations by collaborating robot teams
- 2021
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Ingår i: Paladyn - Journal of Behavioral Robotics. - : De Gruyter Open. - 2080-9778 .- 2081-4836. ; 12:1, s. 47-57
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we present work on collaborating robot teams that use verbal explanations of their actions and intentions in order to be more understandable to the human. For this, we introduce a mechanism that determines what information the robots should verbalize in accordance with Grice’s maxim of quantity, i.e., convey as much information as is required and no more or less. Our setup is a robot team collaborating to achieve a common goal while explaining in natural language what they are currently doing and what they intend to do. The proposed approach is implemented on three Pepper robots moving objects on a table. It is evaluated by human subjects answering a range of questions about the robots’ explanations, which are generated using either our proposed approach or two further approaches implemented for evaluation purposes. Overall, we find that our proposed approach leads to the most understanding of what the robots are doing. In addition, we further propose a method for incorporating policies driving the distribution of tasks among the robots, which may further support understandability.
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| 6. |
- Norinder, Ulf, 1956-, et al.
(författare)
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Conformal prediction to define applicability domain : A case study on predicting ER and AR binding
- 2016
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Ingår i: SAR and QSAR in environmental research (Print). - : Taylor & Francis. - 1062-936X .- 1029-046X. ; 27:4, s. 303-316
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Tidskriftsartikel (refereegranskat)abstract
- A fundamental element when deriving a robust and predictive in silico model is not only the statistical quality of the model in question but, equally important, the estimate of its predictive boundaries. This work presents a new method, conformal prediction, for applicability domain estimation in the field of endocrine disruptors. The method is applied to binders and non-binders related to the oestrogen and androgen receptors. Ensembles of decision trees are used as statistical method and three different sets (dragon, rdkit and signature fingerprints) are investigated as chemical descriptors. The conformal prediction method results in valid models where there is an excellent balance in quality between the internally validated training set and the corresponding external test set, both in terms of validity and with respect to sensitivity and specificity. With this method the level of confidence can be readily altered by the user and the consequences thereof immediately inspected. Furthermore, the predictive boundaries for the derived models are rigorously defined by using the conformal prediction framework, thus no ambiguity exists as to the level of similarity needed for new compounds to be in or out of the predictive boundaries of the derived models where reliable predictions can be expected.
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| 7. |
- Richter, Kai-Florian, et al.
(författare)
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Current topics and challenges in geoAI
- 2023
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Ingår i: Künstliche Intelligenz. - : Springer Nature. - 0933-1875 .- 1610-1987. ; 37, s. 11-16
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Tidskriftsartikel (refereegranskat)abstract
- Taken literally, geoAI is the use of Artificial Intelligence methods and techniques in solving geo-spatial problems. Similar to AI more generally, geoAI has seen an influx of new (big) data sources and advanced machine learning techniques, but also a shift in the kind of problems under investigation. In this article, we highlight some of these changes and identify current topics and challenges in geoAI.
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| 8. |
- Richter, Kai-Florian, et al.
(författare)
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Icon-based Navigation
- 2018
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Ingår i: Geospatial Technologies for All. - Lund : Lund University. - 9783319782089
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Konferensbidrag (refereegranskat)abstract
- Icon-based navigation uses a minimalist approach to mobile navigation assistance by offering navigators only icon displays representing landmark objects at waypoints along a route in an indoor environment. In this paper, we motivate this new concept and its usefulness, present a first prototype implementation exploring the concept, and results of an initial empirical evaluation. While results are not fully conclusive, they point to the potential of this kind of navigation assistance.
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| 9. |
- Richter, Kai-Florian, et al.
(författare)
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Inside an autonomous car : some open issues and social implications
- 2023
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Ingår i: CarSA Workshop. - : Association for Computing Machinery (ACM).
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Konferensbidrag (refereegranskat)abstract
- Driving is a highly social activity with various interactions between the different actors involved in traffic. Autonomous vehicles will pose several challenges to the social fabric of traffic and, as most new technology, will lead to changes in human behavior. This will surely hold for interactions between autonomous vehicles and actors \emph{outside} the vehicle. However and importantly, autonomous vehicles will also alter existing and introduce new social situations and interactions for those \emph{inside} the vehicle, which appears to be an under-researched topic. This paper will focus on the passengers of autonomous vehicles. We will discuss some of the implications and expected changes in the relationship between a car and those inside it, and highlight some of the open issues of being enclosed and driven by a highly complex, largely black-box AI system on wheels.
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| 10. |
- Kashian, Alireza, et al.
(författare)
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Automatic analysis of positional plausibility for points of interest in OpenStreetMap using coexistence patterns
- 2019
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Ingår i: International Journal of Geographical Information Science. - : Taylor & Francis Group. - 1365-8816 .- 1365-8824 .- 1362-3087. ; 33:7, s. 1420-1443
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Tidskriftsartikel (refereegranskat)abstract
- In the past decade, Volunteered Geographic Information (VGI) has emerged as a new source of geographic information, making it a cheap and universal competitor to existing authoritative data sources. The growing popularity of VGI platforms, such as OpenStreetMap (OSM), would trigger malicious activities such as vandalism or spam. Similarly, wrong entries by unexperienced contributors adds to the complexities and directly impact the reliability of such databases. While there are some existing methods and tools for monitoring OSM data quality, there is still a lack of advanced mechanisms for automatic validation. This paper presents a new recommender tool which evaluates the positional plausibility of incoming POI registrations in OSM by generating near real-time validation scores. Similar to machine learning techniques, the tool discovers, stores and reapplies binary distance-based coexistence patterns between one specific POI and its surrounding objects. To clarify the idea, basic concepts about analysing coexistence patterns including design methodology and algorithms are covered in this context. Furthermore, the results of two case studies are presented to demonstrate the analytical power and reliability of the proposed technique. The encouraging results of this new recommendation tool elevates the need for developing reliable quality assurance systems in OSM and other VGI projects.
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