XAI: Using Smart Photobooth for Explaining History of Art

in XAI: Using Smart Photobooth for Explaining History of Art (2022, December)

The rise of Artificial Intelligence has led to advancements in daily life, including applications in industries, telemedicine, farming, and smart cities. It is necessary to have human-AI synergies to ... [more ▼]

The rise of Artificial Intelligence has led to advancements in daily life, including applications in industries, telemedicine, farming, and smart cities. It is necessary to have human-AI synergies to guarantee user engagement and provide interactive expert knowledge, despite AI’s success in "less technical" fields. In this article, the possible synergies between humans and AI to explain the development of art history and artistic style transfer are discussed. This study is part of the "Smart Photobooth" project that is able to automatically transform a user’s picture into a well-known artistic style as an interactive approach to introduce the fundamentals of the history of art to the common people and provide them with a concise explanation of the various art painting styles. This study investigates human-AI synergies by combining the explanation produced by an explainable AI mechanism with a human expert’s insights to provide reasons for school students and a larger audience. [less ▲]

Deep Mining Covid-19 Literature

in Applied Informatics, 5th International Conference, ICAI 2022, Arequipa, Peru, October 27–29, 2022, Proceedings (2022)

In this paper we investigate how scientific and medical papers about Covid-19 can be effectively mined. For this purpose we use the CORD19 dataset which is a huge collection of all papers published about ... [more ▼]

In this paper we investigate how scientific and medical papers about Covid-19 can be effectively mined. For this purpose we use the CORD19 dataset which is a huge collection of all papers published about and around the SARS-CoV2 virus and the pandemic it caused. We discuss how classical text mining algorithms like Latent Semantic Analysis (LSA) or its modern version Latent Drichlet Allocation (LDA) can be used for this purpose and also touch more modern variant of these algorithms like word2vec which came with deep learning wave and show their advantages and disadvantages each. We finish the paper with showing some topic examples from the corpus and answer questions such as which topics are the most prominent for the corpus or how many percentage of the corpus is dedicated to them. We also give a discussion of how topics around RNA research in connection with Covid-19 can be examined. [less ▲]

About AI and Arts

Speeches/Talks (2021)

From a technical point of view, one can say that there have been extraordinary developments in the broad areas of Artificial Intelligence and Data Science that increasingly determine our lives. Think, for ... [more ▼]

From a technical point of view, one can say that there have been extraordinary developments in the broad areas of Artificial Intelligence and Data Science that increasingly determine our lives. Think, for example, of the many intelligent assistants that are playing an ever greater role in road traffic, in hospitals and in many other areas of application. Art is affected by this as well, because the computer-assisted and AI-supported implementation of creative ideas and thoughts and experimentation with new things have led to innovative results. [less ▲]

The Future of Living with AI

Speeches/Talks (2021)

This talk, which was part of a 2-hour panel and delivered as a 20-minute presentation without slides, came at the invitation of the Luxembourg Embassy in Brussels, Belgium. The speech is a statement and ... [more ▼]

This talk, which was part of a 2-hour panel and delivered as a 20-minute presentation without slides, came at the invitation of the Luxembourg Embassy in Brussels, Belgium. The speech is a statement and part of the International Symposium "The Future of Living", supported by EUNIC - EU National Institutes of Culture. The event was under the patronage of the Slovenian Presidency of the European Parliament. In the lecture, I briefly presented some selected ideas, observations, and examples on the symposium topic as well as my view of a future living together. [less ▲]

Ist die Künstliche Intelligenz für oder gegen die Menschheit?

Speeches/Talks (2021)

La Commission Luxembourgeoise pour la coopération avec l’UNESCO et la Bibliothèque nationale du Luxembourg invitent à leur cycle de conférences dans le cadre des « Rendez-Vous de l’UNESCO ». Le thème ... [more ▼]

La Commission Luxembourgeoise pour la coopération avec l’UNESCO et la Bibliothèque nationale du Luxembourg invitent à leur cycle de conférences dans le cadre des « Rendez-Vous de l’UNESCO ». Le thème central du cycle est cette année : « Mankind and Media. Rethinking the Roles in the Age of Information » Les dernières années ont en outre montré clairement qu’on est fortement dépendant de la transmission des informations vite et performante : on demande toujours plus de données, plus d’informations, plus de connectivité. Mais peut-on conserver une vue d’ensemble dans ce flux d’information hyperrapide ? Peut-on encore contrôler la transformation des informations par les médias numériques ? Où en est l’humain devant l’évolution exponentielle des technologies, de l’intelligence artificielle et du commerce de nos données ? Qui reste à l’origine de l’information et qui comment nous l’interprétons ? Les conférences traitent cette thématique en différentes perspectives. Le 25 février, Prof. Dr. Christoph Schommer de l’Université du Luxembourg fera l’ouverture en posant la question : L’intelligence Artificielle? Où en sommes-nous ? Il abordera les possibilités, chances et risques de ces nouvelles technologies. 4 journalistes se réuniront le 22 avril et discuteront, animés par Josée Hansen, la transmission d’informations et l’objectivité dans le temps des « Fake News » et du « Click Bait ». Dr. Manuela di Franco nous introduira le 1er juillet dans le monde des dessins animés et se penchera sur leur rôle dans la transmission des messages subliminaux et propagandistes. Ian di Toffoli et Prof. Dr. Lukas K. Sosoe s’entretiendront le 30 septembre sur les problèmes et limites de l’éthique dans le monde digital. Qu’il ne faut pas oublier l’art dans la transmission des messages nous rappelleront les 4 artistes qui poursuivront le 2nd décembre, dans la dernière table ronde de ce cycle modérée par Dr. Nora Schleich, le rôle de la liberté artistique face à la libre expression des opinions. Que peut et même doit faire l’art ? La Bibliothèque nationale du Luxembourg aménagera pour chacune de ces soirées, qui auront lieu toujours jeudi à 19hrs, une salle assez grande pour assurer la réunion en présence physique et, le cas échéant, en respect des restrictions actuelles. 25.02.2021 Der Mensch und die Künstliche Intelligenz. Wo stehen wir? (DE) Un entretien avec Prof. Christoph Schommer, modéré par Dr. Nora Schleich, traduit en anglais 22.04.2021 Mediepluralismus – Eng Garantie fir Demokratie am 21. Joerhonnert? (LU) Une table-ronde avec François Aulner, Pia Oppel, Christoph Bumb et Jean-Louis Siweck, modérée par Josée Hansen 01.07.2021 Transmission of Information via Specific Media – Propagandistic Messages in Comics (EN) Une présentation de Dr. Manuela di Franco, traduit en français 30.09.2021 L’Ethique dans la société de l’Information (FR) Un discours avec Prof. Lukas Sosoe, modéré par Ian de Toffoli, traduit en anglais 02.12.2021 Artistesch Fräiheet a Meenungsfräiheet (LU) Une table-ronde avec Justine Blau, Dr. Cédric Kayer, Filip Markiewicz et Anne Simon., modérée par Dr. Nora Schleich Comme les places sont limitées, il faudra s’inscrire au plus tard trois jours avant la conférence en envoyant un courriel à : reservation@bnl.etat.lu Pour plus d’informations, veuillez accéder le site internet : www.unesco.lu; www.bnl.lu [less ▲]

Proceedings of the AI4Health Lecture Series (2021)

Scientific Conference (2021)

The research field between Artificial Intelligence and Health sciences has established itself as a central research direction in recent years and has also further increased social interest. On the one ... [more ▼]

The research field between Artificial Intelligence and Health sciences has established itself as a central research direction in recent years and has also further increased social interest. On the one hand, this is due to the emergence of medical mass data and their use for AI-related fields, such as machine learning, human-computer interfaces and natural language-processing systems, and on the other hand, it is also due to the steadily growing social interest, which is not determined by the current Covid 19 pandemic. To this end, the lecture series is intended to provide an opportunity for scientific exchange. [less ▲]

Building up Explainability in Multi-layer Perceptrons for Credit Risk Modeling

in Sharma, Rudrani (Ed.) Building up Explainability in Multi-layer Perceptrons for Credit Risk Modeling (2020, October 09)

Granting loans is one of the major concerns of financial institutions due to the risks of default borrowers. Default prediction by the neural networks is a popular technique for credit risk modeling ... [more ▼]

Granting loans is one of the major concerns of financial institutions due to the risks of default borrowers. Default prediction by the neural networks is a popular technique for credit risk modeling. Neural networks generally offer the accurate predictions that help banks to prevent financial losses and grow their business by approving more creditworthy borrowers. Although neural networks are capable of capturing the complex, non-linear relationships between a large number of features and output, these models act as black boxes. This is a graduation project paper that is focused on loan default risk prediction by multi-layer perceptron neural network and building up explainability to some degree in the trained neural networks through sensitivity analysis. The architecture of a multi-layer perceptron neural network with the best result is used to help the credit-risk manager in explaining why an applicant is a defaulter or non-defaulter. The prediction of a trained multi-layer perceptron neural network is explained by mapping input features and target variables directly using a model-agnostic explanation as well as a modelspecific explanation. Lastly, a comparison is performed between two explanation methods. [less ▲]

An Annotation Framework for Luxembourgish Sentiment Analysis

in Besacier, Laurent; Sakti, Sakriani; Soria, Claudia (Eds.) et al Proceedings of the LREC 2020 1st Joint SLTU and CCURL Workshop (SLTU-CCURL 2020) (2020, May)

The aim of this paper is to present a framework developed for crowdsourcing sentiment annotation for the low-resource language Luxembourgish. Our tool is easily accessible through a web interface and ... [more ▼]

The aim of this paper is to present a framework developed for crowdsourcing sentiment annotation for the low-resource language Luxembourgish. Our tool is easily accessible through a web interface and facilitates sentence-level annotation of several annotators in parallel. In the heart of our framework is an XML database, which serves as central part linking several components. The corpus in the database consists of news articles and user comments. One of the components is LuNa, a tool for linguistic preprocessing of the data set. It tokenizes the text, splits it into sentences and assigns POS-tags to the tokens. After that, the preprocessed text is stored in XML format into the database. The Sentiment Annotation Tool, which is a browser-based tool, then enables the annotation of split sentences from the database. The Sentiment Engine, a separate module, is trained with this material in order to annotate the whole data set and analyze the sentiment of the comments over time and in relationship to the news articles. The gained knowledge can again be used to improve the sentiment classification on the one hand and on the other hand to understand the sentiment phenomenon from the linguistic point of view. [less ▲]

Eine Doktorarbeit zu beginnen, ist (relativ) leicht...

Article for general public (2020)

Vor einigen Wochen war es wieder soweit: Zwei Doktorandinnen hatten ihre wissenschaftlichen Arbeiten eingereicht, sich den Fragen einer internationalen Expertenkommission gestellt, und schließlich ihre ... [more ▼]

Vor einigen Wochen war es wieder soweit: Zwei Doktorandinnen hatten ihre wissenschaftlichen Arbeiten eingereicht, sich den Fragen einer internationalen Expertenkommission gestellt, und schließlich ihre Doktorarbeiten verteidigt. [less ▲]

Speech Based Estimation of Parkinson’s Disease Using Gaussian Processes and Automatic Relevance Determination

in Neurocomputing (2020), 401

Parkinson’s disease is a progressive neurodegenerative disorder often accompanied by impairment in articulation, phonation, prosody and fluency of speech. In fact, speech impairment is one of the earliest ... [more ▼]

Parkinson’s disease is a progressive neurodegenerative disorder often accompanied by impairment in articulation, phonation, prosody and fluency of speech. In fact, speech impairment is one of the earliest Parkinson’s disease symptoms, and may be used for early diagnosis. We present an experimental study of identification of Parkinson’s disease and assessment of disease progress from speech using Gaussian processes, which is further combined with Automatic Relevance Determination (ARD) for efficient feature selection. Hyperparameters of ARD covariance functions are learned for each individual feature; therefore, can be used for evaluation of their importance. In that way only a small subset of highly relevant acoustic features is selected, leading to models with better performance and lower complexity. The performance of the proposed method was assessed on two datasets: Parkinson’s disease detection dataset, which contains a range of biomedical voice measurements obtained from 31 subjects, 23 of them suffering from Parkinson’s disease and 8 healthy subjects; and Parkinson’s telemonitoring dataset, containing biomedical voice measurements collected from 42 Parkinson’s disease patients for estimation of the disease progress. Gaussian process classification with automatic relevance determination is able to successfully discriminate between Parkinson’s disease patients and healthy controls with 96.92% accuracy, outperforming Support Vector Machines and decision tree ensembles (random forests, boosted and bagged decision trees). The usability of Gaussian processes is further confirmed in regression task for tracking the progress of the disease. [less ▲]