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Search Results (3)

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Keywords = familiar and unfamiliar face recognition

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17 pages, 754 KiB  
Article
A Dynamic Multi-Scale Convolution Model for Face Recognition Using Event-Related Potentials
by Shengkai Li, Tonglin Zhang, Fangmei Yang, Xian Li, Ziyang Wang and Dongjie Zhao
Sensors 2024, 24(13), 4368; https://doi.org/10.3390/s24134368 - 5 Jul 2024
Viewed by 1299
Abstract
With the development of data mining technology, the analysis of event-related potential (ERP) data has evolved from statistical analysis of time-domain features to data-driven techniques based on supervised and unsupervised learning. However, there are still many challenges in understanding the relationship between ERP [...] Read more.
With the development of data mining technology, the analysis of event-related potential (ERP) data has evolved from statistical analysis of time-domain features to data-driven techniques based on supervised and unsupervised learning. However, there are still many challenges in understanding the relationship between ERP components and the representation of familiar and unfamiliar faces. To address this, this paper proposes a model based on Dynamic Multi-Scale Convolution for group recognition of familiar and unfamiliar faces. This approach uses generated weight masks for cross-subject familiar/unfamiliar face recognition using a multi-scale model. The model employs a variable-length filter generator to dynamically determine the optimal filter length for time-series samples, thereby capturing features at different time scales. Comparative experiments are conducted to evaluate the model’s performance against SOTA models. The results demonstrate that our model achieves impressive outcomes, with a balanced accuracy rate of 93.20% and an F1 score of 88.54%, outperforming the methods used for comparison. The ERP data extracted from different time regions in the model can also provide data-driven technical support for research based on the representation of different ERP components. Full article
(This article belongs to the Section Sensing and Imaging)
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19 pages, 2442 KiB  
Article
Neural Correlates of Voice Learning with Distinctive and Non-Distinctive Faces
by Romi Zäske, Jürgen M. Kaufmann and Stefan R. Schweinberger
Brain Sci. 2023, 13(4), 637; https://doi.org/10.3390/brainsci13040637 - 7 Apr 2023
Cited by 2 | Viewed by 2375
Abstract
Recognizing people from their voices may be facilitated by a voice’s distinctiveness, in a manner similar to that which has been reported for faces. However, little is known about the neural time-course of voice learning and the role of facial information in voice [...] Read more.
Recognizing people from their voices may be facilitated by a voice’s distinctiveness, in a manner similar to that which has been reported for faces. However, little is known about the neural time-course of voice learning and the role of facial information in voice learning. Based on evidence for audiovisual integration in the recognition of familiar people, we studied the behavioral and electrophysiological correlates of voice learning associated with distinctive or non-distinctive faces. We repeated twelve unfamiliar voices uttering short sentences, together with either distinctive or non-distinctive faces (depicted before and during voice presentation) in six learning-test cycles. During learning, distinctive faces increased early visually-evoked (N170, P200, N250) potentials relative to non-distinctive faces, and face distinctiveness modulated voice-elicited slow EEG activity at the occipito–temporal and fronto-central electrodes. At the test, unimodally-presented voices previously learned with distinctive faces were classified more quickly than were voices learned with non-distinctive faces, and also more quickly than novel voices. Moreover, voices previously learned with faces elicited an N250-like component that was similar in topography to that typically observed for facial stimuli. The preliminary source localization of this voice-induced N250 was compatible with a source in the fusiform gyrus. Taken together, our findings provide support for a theory of early interaction between voice and face processing areas during both learning and voice recognition. Full article
(This article belongs to the Special Issue People Recognition through Face, Voice, Name and Their Interactions)
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17 pages, 731 KiB  
Article
Objective Patterns of Face Recognition Deficits in 165 Adults with Self-Reported Developmental Prosopagnosia
by Sarah Bate, Rachel J. Bennetts, Nicola Gregory, Jeremy J. Tree, Ebony Murray, Amanda Adams, Anna K. Bobak, Tegan Penton, Tao Yang and Michael J. Banissy
Brain Sci. 2019, 9(6), 133; https://doi.org/10.3390/brainsci9060133 - 6 Jun 2019
Cited by 43 | Viewed by 8272
Abstract
In the last 15 years, increasing numbers of individuals have self-referred to research laboratories in the belief that they experience severe everyday difficulties with face recognition. The condition “developmental prosopagnosia” (DP) is typically diagnosed when impairment is identified on at least two objective [...] Read more.
In the last 15 years, increasing numbers of individuals have self-referred to research laboratories in the belief that they experience severe everyday difficulties with face recognition. The condition “developmental prosopagnosia” (DP) is typically diagnosed when impairment is identified on at least two objective face-processing tests, usually involving assessments of face perception, unfamiliar face memory, and famous face recognition. While existing evidence suggests that some individuals may have a mnemonic form of prosopagnosia, it is also possible that other subtypes exist. The current study assessed 165 adults who believe they experience DP, and 38% of the sample were impaired on at least two of the tests outlined above. While statistical dissociations between face perception and face memory were only observed in four cases, a further 25% of the sample displayed dissociations between impaired famous face recognition and intact short-term unfamiliar face memory and face perception. We discuss whether this pattern of findings reflects (a) limitations within dominant diagnostic tests and protocols, (b) a less severe form of DP, or (c) a currently unrecognized but prevalent form of the condition that affects long-term face memory, familiar face recognition or semantic processing. Full article
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