Results 31 to 40 of about 161,242 (287)

Preference learning for affective modeling [PDF]

, 2009
There is an increasing trend towards personalization of services and interaction. The use of computational models for learning to predict user emotional preferences is of significant importance towards system personalization.
3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, Yannakakis, Georgios N.   +1 more
core   +1 more source

Machine Understanding of Human Behavior [PDF]

, 2007
A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing,
Huang, Thomas, Nijholt, Anton, Pantic, Maja, Pentland, Alex   +3 more
core   +7 more sources

Drug-Drug Interaction Extraction Based on Transfer Weight Matrix and Memory Network

IEEE Access, 2019
Extracting drug-drug interaction (DDI) in the text is the process of identifying how two target drugs in a given sentence interact. Previous methods, which were limited to conventional machine learning techniques, we are susceptible to issues such as ...
Juan Liu, Zhong Huang, Fuji Ren, Lei Hua
doaj   +1 more source

A Cognitive Architecture for the Implementation of Emotions in Computing Systems

, 2016
In this paper we present a new neurobiologically-inspired affective cognitive architecture: NEUCOGAR (NEUromodulating COGnitive ARchitecture). The objective of NEUCOGAR is the identification of a mapping from the influence of serotonin, dopamine and ...
Distefano, Salvatore, Mazzara, Manuel, Nurgaliev, Ildar, Talanov, Max, Tchitchigin, Alexander, Vallverdú, Jordi   +5 more
core   +1 more source

Unveiling Affective Signals [PDF]

, 2010
The ability to process and, subsequently, understand affective signals is the core of emotional intelligence and empathy. However, more than a decade of research in affective computing has shown that it is hard to develop computational models of this ...
Broek, Egon L. van den, Nijholt, Anton, Westerink, Joyce H.D.M.   +2 more
core   +2 more sources

MobileSteelNet: A Lightweight Steel Surface Defect Classification Network with Cross-Interactive Efficient Multi-Scale Attention

Sensors
Steel surface defect classification is critical for industrial quality control, yet existing methods struggle to balance accuracy and efficiency for real-time deployment in vision-based sensor systems.
Xiang Zou, Zhongming Liu, Chengjun Xu, Jiawei Zhang, Zhaoyu Li   +4 more
doaj   +1 more source

Multi-modal Approach for Affective Computing

, 2018
Throughout the past decade, many studies have classified human emotions using only a single sensing modality such as face video, electroencephalogram (EEG), electrocardiogram (ECG), galvanic skin response (GSR), etc.
Jung, Tzyy-Ping, Sejnowski, Terrence J., Siddharth, Siddharth   +2 more
core   +1 more source

Towards general models of player affect [PDF]

, 2017
While the primary focus of affective computing has been on constructing efficient and reliable models of affect, the vast majority of such models are limited to a specific task and domain. This paper, instead, investigates how computational models of
Camilleri, Elizabeth, Liapis, Antonios, Seventh International Conference on Affective Computing and Intelligent Interaction, Yannakakis, Georgios N.   +3 more
core   +1 more source

Effects of Musical Tempo on Musicians’ and Non-musicians’ Emotional Experience When Listening to Music

Frontiers in Psychology, 2018
Tempo is an important musical element that affects human’s emotional processes when listening to music. However, it remains unclear how tempo and training affect individuals’ emotional experience of music.
Ying Liu, Ying Liu, Ying Liu, Guangyuan Liu, Guangyuan Liu, Guangyuan Liu, Guangyuan Liu, Guangyuan Liu, Dongtao Wei, Dongtao Wei, Dongtao Wei, Qiang Li, Qiang Li, Qiang Li, Guangjie Yuan, Guangjie Yuan, Guangjie Yuan, Shifu Wu, Shifu Wu, Shifu Wu, Gaoyuan Wang, Xingcong Zhao, Xingcong Zhao, Xingcong Zhao   +23 more
doaj   +1 more source

Hyperbolic trade-off: The importance of balancing trial and subject sample sizes in neuroimaging

NeuroImage, 2022
Here we investigate the crucial role of trials in task-based neuroimaging from the perspectives of statistical efficiency and condition-level generalizability. Big data initiatives have gained popularity for leveraging a large sample of subjects to study
Gang Chen, Daniel S. Pine, Melissa A. Brotman, Ashley R. Smith, Robert W. Cox, Paul A. Taylor, Simone P. Haller   +6 more
doaj   +1 more source