Outputs (35)

GPT4 : The Ultimate Brain (2022)
Preprint / Working Paper
Adesso, G. GPT4 : The Ultimate Brain

We introduce a powerful general probabilistic theory, GPT4, that extends classical and quantum theories to include higher-dimensional probabilistic models. GPT4 results from the four-fold integration of GPT in physics (Generalized Probabilistic T... Read More about GPT4 : The Ultimate Brain.

Designing for Trust: Autonomous Animal-Centric Robotic & AI Systems (2022)
Presentation / Conference Contribution
Chamberlain, A., Benford, S., Fischer, J., Barnard, P., Greenhalgh, C., Row Farr, J., Tandavanitj, N., & Adams, M. (2022, December). Designing for Trust: Autonomous Animal-Centric Robotic & AI Systems. Presented at Proceedings of the Ninth International Conference on Animal-Computer Interaction, Newcastle, UK

From cat feeders and cat flaps to robot toys, humans are deploying increasingly autonomous systems to look after their pets. In parallel, industry is developing the next generation of autonomous systems to look after humans in the home – most notably... Read More about Designing for Trust: Autonomous Animal-Centric Robotic & AI Systems.

ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments (2022)
Presentation / Conference Contribution
Fatehi, K., Torres, M. T., & Kucukyilmaz, A. (2022, September). ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments. Presented at Interspeech 2022, Incheon, Korea

Recent improvements in Automatic Speech Recognition (ASR) systems obtain extraordinary results. However, there are specific domains where training data can be either limited or not representative enough, which are known as Low-Resource Environments (... Read More about ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments.

A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation (2022)
Journal Article
Borsci, S., Schmettow, M., Malizia, A., Chamberlain, A., & van der Velde, F. (2023). A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation. Personal and Ubiquitous Computing, 27, 317–330. https://doi.org/10.1007/s00779-022-01690-0

The Bot Usability Scale (BUS) is a standardised tool to assess and compare the satisfaction of users after interacting with chatbots to support the development of usable conversational systems. The English version of the 15-item BUS scale (BUS-15) wa... Read More about A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation.

Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning (2022)
Presentation / Conference Contribution
Serhan, B., Pandya, H., Kucukyilmaz, A., & Neumann, G. (2022, May). Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning. Presented at 2022 IEEE International Conference on Robotics and Automation (ICRA 2022), Philadelphia, USA

Efficient robotic manipulation of objects for sorting and searching often rely upon how well the objects are perceived and the available grasp poses. The challenge arises when the objects are irregular, have similar visual features (e.g., textureless... Read More about Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning.

Metaverse: The Vision for the Future (2022)
Presentation / Conference Contribution
Xu, J., Papangelis, K., Dunham, J., Goncalves, J., LaLone, N. J., Chamberlain, A., Lykourentzou, I., Vinella, F. L., & Schwartz, D. I. (2022, April). Metaverse: The Vision for the Future. Presented at CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, USA

In recent years, the notion of the Metaverse has become the focus of a growing body of work in the industry. However, there is no consensus on the conceptualization in academia. To date, much of this attention has revolved around technological challe... Read More about Metaverse: The Vision for the Future.

ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies (2021)
Presentation / Conference Contribution
Galvez Trigo, M. J., Porcheron, M., Egede, J., Fischer, J. E., Hazzard, A., Greenhalgh, C., Bodiaj, E., & Valstar, M. (2021, July). ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies. Presented at CUI 2021 : Third Conference on Conversational User Interfaces, Bilbao (online), Spain

We present ALTCAI, a Wizard of Oz Embodied Conversational Agent that has been developed to explore the use of interactive agents as an effective and engaging tool for delivering health and well-being advice to expectant and nursing mothers in Nigeria... Read More about ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies.

Teachers’ Perspectives on the Adoption of an Adaptive Learning System Based on Multimodal Affect Recognition for Students with Learning Disabilities and Autism (2021)
Presentation / Conference Contribution
Standen, P. J., Brown, D. J., Kwiatkowska, G. M., Belmonte, M. K., Galvez Trigo, M. J., Boulton, H., Burton, A., Hallewell, M. J., Shopland, N., Blanco Gonzalez, M. A., Milli, E., Cobello, S., Mazzucato, A., & Traversi, M. (2021, July). Teachers’ Perspectives on the Adoption of an Adaptive Learning System Based on Multimodal Affect Recognition for Students with Learning Disabilities and Autism. Presented at International Conference on Adaptive Instructional Systems (AIS 2021), Virtual Event

Adoption of e-learning for those with special needs lags that for mainstream learners. Not much is known about barriers and facilitators that drive this disparity. The present study used focus groups and interviews to collect the views of 21 teachers... Read More about Teachers’ Perspectives on the Adoption of an Adaptive Learning System Based on Multimodal Affect Recognition for Students with Learning Disabilities and Autism.

Improving Uncertainty Estimation With Semi-supervised Deep Learning for COVID-19 Detection Using Chest X-ray Images (2021)
Journal Article
Calderon-Ramirez, S., Yang, S., Moemeni, A., Colreavy-Donnelly, S., Elizondo, D. A., Oala, L., Rodríguez-Capitán, J., Jiménez-Navarro, M., López-Rubio, E., & Molina-Cabello, M. A. (2021). Improving Uncertainty Estimation With Semi-supervised Deep Learning for COVID-19 Detection Using Chest X-ray Images. IEEE Access, 9, 85442 - 85454. https://doi.org/10.1109/ACCESS.2021.3085418

In this work we implement a COVID-19 infection detection system based on chest Xray images with uncertainty estimation. Uncertainty estimation is vital for safe usage of computer aided diagnosis tools in medical applications. Model estimations with h... Read More about Improving Uncertainty Estimation With Semi-supervised Deep Learning for COVID-19 Detection Using Chest X-ray Images.

From AI, creativity and music to IoT, HCI, musical instrument design and audio interaction: a journey in sound (2021)
Journal Article
(2021). From AI, creativity and music to IoT, HCI, musical instrument design and audio interaction: a journey in sound. Personal and Ubiquitous Computing, 25(4), 617-620. https://doi.org/10.1007/s00779-021-01554-z

This introduction brings together a range of research, a majority of which was presented at the Audio Mostly conference hosted at the University of Nottingham. The conference brings together a range of researchers, industry, designers and educators t... Read More about From AI, creativity and music to IoT, HCI, musical instrument design and audio interaction: a journey in sound.

Intelligent control of exoskeletons through a novel learning-from-demonstration method (2020)
Presentation / Conference Contribution
Ugur, E., Samur, E., Ugurlu, B., Erol Barkana, D., Kucukyilmaz, A., & Bebek, O. (2020, September). Intelligent control of exoskeletons through a novel learning-from-demonstration method. Poster presented at Cybathlon Symposium 2020, Zurich, Switzerland

We present a novel concept that enables the intelligent and adaptive control of exoskeletons through exploiting our state-of-the-art learning from demonstration (LfD) method, namely Conditional Neural Movement Primitives (CNMPs) [1], on our integrate... Read More about Intelligent control of exoskeletons through a novel learning-from-demonstration method.

Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling (2019)
Journal Article
Gibbs, J., French, A., Murchie, E., Wells, D., Pound, M., & Pridmore, T. (2020). Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(6), 1907-1917. https://doi.org/10.1109/TCBB.2019.2896908

Plant phenotyping is the quantitative description of a plant’s physiological, biochemical and anatomical status which can be used in trait selection and helps to provide mechanisms to link underlying genetics with yield. Here, an active vision- based... Read More about Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling.

“It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency (2019)
Journal Article
Webb, H., Patel, M., Rovatsos, M., Davoust, A., Ceppi, S., Koene, A., Dowthwaite, L., Portillo, V., Jirotka, M., & Cano, M. (2019). “It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency. Journal of Information, Communication and Ethics in Society, 17(2), 210-228. https://doi.org/10.1108/jices-11-2018-0092

Purpose
The purpose of this paper is to report on empirical work conducted to open up algorithmic interpretability and transparency. In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorithms and the impac... Read More about “It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency.

Hyper-heuristics: theory and applications (2018)
Book
Pillay, N., & Qu, R. (2018). Hyper-heuristics: theory and applications. Springer Nature. https://doi.org/10.1007/978-3-319-96514-7

This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, pro... Read More about Hyper-heuristics: theory and applications.

Model checking for Coalition Announcement Logic (2018)
Presentation / Conference Contribution
Galimullin, R., Alechina, N., & van Ditmarsch, H. (2018, September). Model checking for Coalition Announcement Logic. Presented at KI 2018: Advances in Artificial Intelligence, Berlin, Germany

Coalition Announcement Logic (CAL) studies how a group of agents can enforce a certain outcome by making a joint announcement, regardless of any announcements made simultaneously by the opponents. The logic is useful to model imperfect information ga... Read More about Model checking for Coalition Announcement Logic.