Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Nikhil Churamani"'
Publikováno v:
Frontiers in Robotics and AI, Vol 9 (2022)
Collaborative interactions require social robots to share the users’ perspective on the interactions and adapt to the dynamics of their affective behaviour. Yet, current approaches for affective behaviour generation in robots focus on instantaneous
Externí odkaz:
https://doaj.org/article/9e39c25254be4f678928b0f553719ae4
Autor:
Marc Pickett, Zheda Mai, German Ignacio Parisi, Davide Maltoni, Quentin Jodelet, Massimo Caccia, Nikhil Churamani, Qi She, Lorenzo Pellegrini, Yu Chen, Issam H. Laradji, Vincenzo Lomonaco, Pau Rodríguez, Ruiping Wang, David Vazquez
Publikováno v:
Artificial Intelligence. 303:103635
In the last few years, we have witnessed a renewed and fast-growing interest in continual learning with deep neural networks with the shared objective of making current AI systems more adaptive, efficient and autonomous. However, despite the signific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38796e4705b92946c33032bd6155c5b4
https://doi.org/10.1016/j.artint.2021.103635
https://doi.org/10.1016/j.artint.2021.103635
Publikováno v:
RO-MAN
Social robots are becoming incorporated in daily human lives, assisting in the promotion of the physical and mental wellbeing of individuals. To investigate the design and use of social robots for delivering mindfulness training, we develop a teleope
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10b5087715698918071475c5fad82139
Most state-of-the-art approaches for Facial Action Unit (AU) detection rely upon evaluating facial expressions from static frames, encoding a snapshot of heightened facial activity. In real-world interactions, however, facial expressions are usually
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::06b25d108967897195ec4fb41f967747
https://zenodo.org/record/6530230
https://zenodo.org/record/6530230
Publikováno v:
RO-MAN
Creating and sustaining closed-loop dynamic and social interactions with humans require robots to continually adapt towards their users' behaviours, their affective states and moods while keeping them engaged in the task they are performing. Analysin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::175383d1811b8127bc938f177cac0f1e
Publikováno v:
2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)
FG
FG
Current state-of-the-art models for automatic FER are based on very deep neural networks that are difficult to train. This makes it challenging to adapt these models to changing conditions, a requirement from FER models given the subjective nature of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88f04905ce764e0944f37690732320fc
Publikováno v:
ACII
Processing human affective behavior is important for developing intelligent agents that interact with humans in complex interaction scenarios. A large number of current approaches that address this problem focus on classifying emotion expressions by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bee9b763498956213216b2a2dba087e7
https://doi.org/10.1109/acii.2019.8925530
https://doi.org/10.1109/acii.2019.8925530
Publikováno v:
IJCNN
Human-Robot Interaction (HRI) studies, particularly the ones designed around social robots, use emotions as important building blocks for interaction design. In order to provide a natural interaction experience, these social robots need to recognise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a09f61813b63a5294e4fa7a1f715a64b
https://doi.org/10.1109/ijcnn.2018.8489158
https://doi.org/10.1109/ijcnn.2018.8489158
Autor:
Henrique Siqueira, Alexander Sutherland, Nikhil Churamani, Egor Lakomkin, Pablo Barros, Stefan Wermter
Publikováno v:
IJCNN
2018 International Joint Conference on Neural Networks (IJCNN)
2018 International Joint Conference on Neural Networks (IJCNN)
This paper is the basis paper for the accepted IJCNN challenge One-Minute Gradual-Emotion Recognition (OMG-Emotion) by which we hope to foster long-emotion classification using neural models for the benefit of the IJCNN community. The proposed corpus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10ba112169874ef15babd8e92561d3c5
https://doi.org/10.1109/ijcnn.2018.8489099
https://doi.org/10.1109/ijcnn.2018.8489099
Autor:
Hwei Geok Ng, Johannes Twiefel, Thi Linh Chi Nguyen, Cornelius Weber, Julius Mayer, Nicolás Navarro-Guerrero, Nikhil Churamani, Marc Brugger, Marcus Soll, Waleed Mustafa, Thomas Hummel, Quan Nguyen, Erik Strahl, Paul Anton, Sebastian Springenberg, Sascha Griffiths, Erik Fließwasser, Stefan Wermter, Stefan Heinrich
Publikováno v:
HAI
Advancements in Human-Robot Interaction involve robots being more responsive and adaptive to the human user they are interacting with. For example, robots model a personalised dialogue with humans, adapting the conversation to accommodate the user's
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c986e146af6ed86d720cec595ded2b0
https://doi.org/10.1145/3125739.3125756
https://doi.org/10.1145/3125739.3125756