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Seeing synchrony: A replication of the effects of task-irrelevant social information on perceptions of interpersonal coordination.

Acta psychologica

Macpherson MC, Fay N, Miles LK.
PMID: 32738451
Acta Psychol (Amst). 2020 Sep;209:103140. doi: 10.1016/j.actpsy.2020.103140. Epub 2020 Jul 29.

The display of synchronous behaviour can be both an engaging spectacle and a source of important social information. When understood as a dynamical system, interpersonal synchrony has specific kinematic qualities that have been shown to shape social perceptions. Little...

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Macpherson MC, Fay N, Miles LK. Seeing synchrony: A replication of the effects of task-irrelevant social information on perceptions of interpersonal coordination. Acta Psychol (Amst). 2020;209:103140doi: 10.1016/j.actpsy.2020.103140.
Macpherson, M. C., Fay, N., & Miles, L. K. (2020). Seeing synchrony: A replication of the effects of task-irrelevant social information on perceptions of interpersonal coordination. Acta psychologica, 209103140. https://doi.org/10.1016/j.actpsy.2020.103140
Macpherson, M C, et al. "Seeing synchrony: A replication of the effects of task-irrelevant social information on perceptions of interpersonal coordination." Acta psychologica vol. 209 (2020): 103140. doi: https://doi.org/10.1016/j.actpsy.2020.103140
Macpherson MC, Fay N, Miles LK. Seeing synchrony: A replication of the effects of task-irrelevant social information on perceptions of interpersonal coordination. Acta Psychol (Amst). 2020 Sep;209:103140. doi: 10.1016/j.actpsy.2020.103140. Epub 2020 Jul 29. PMID: 32738451.
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Structure-Coherent Deep Feature Learning for Robust Face Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

Lin C, Zhu B, Wang Q, Liao R, Qian C, Lu J, Zhou J.
PMID: 34038362
IEEE Trans Image Process. 2021;30:5313-5326. doi: 10.1109/TIP.2021.3082319. Epub 2021 Jun 02.

In this paper, we propose a structure-coherent deep feature learning method for face alignment. Unlike most existing face alignment methods which overlook the facial structure cues, we explicitly exploit the relation among facial landmarks to make the detector robust...

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Lin C, Zhu B, Wang Q, et al. Structure-Coherent Deep Feature Learning for Robust Face Alignment. IEEE Trans Image Process. 2021;30:5313-5326doi: 10.1109/TIP.2021.3082319.
Lin, C., Zhu, B., Wang, Q., Liao, R., Qian, C., Lu, J., & Zhou, J. (2021). Structure-Coherent Deep Feature Learning for Robust Face Alignment. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 305313-5326. https://doi.org/10.1109/TIP.2021.3082319
Lin, Chunze, et al. "Structure-Coherent Deep Feature Learning for Robust Face Alignment." IEEE transactions on image processing : a publication of the IEEE Signal Processing Society vol. 30 (2021): 5313-5326. doi: https://doi.org/10.1109/TIP.2021.3082319
Lin C, Zhu B, Wang Q, Liao R, Qian C, Lu J, Zhou J. Structure-Coherent Deep Feature Learning for Robust Face Alignment. IEEE Trans Image Process. 2021;30:5313-5326. doi: 10.1109/TIP.2021.3082319. Epub 2021 Jun 02. PMID: 34038362.
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Locality-Aware Channel-Wise Dropout for Occluded Face Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

He M, Zhang J, Shan S, Liu X, Wu Z, Chen X.
PMID: 34890329
IEEE Trans Image Process. 2022;31:788-798. doi: 10.1109/TIP.2021.3132827. Epub 2022 Jan 06.

Face recognition remains a challenging task in unconstrained scenarios, especially when faces are partially occluded. To improve the robustness against occlusion, augmenting the training images with artificial occlusions has been proved as a useful approach. However, these artificial occlusions...

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He M, Zhang J, Shan S, et al. Locality-Aware Channel-Wise Dropout for Occluded Face Recognition. IEEE Trans Image Process. 2022;31:788-798doi: 10.1109/TIP.2021.3132827.
He, M., Zhang, J., Shan, S., Liu, X., Wu, Z., & Chen, X. (2022). Locality-Aware Channel-Wise Dropout for Occluded Face Recognition. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 31788-798. https://doi.org/10.1109/TIP.2021.3132827
He, Mingjie, et al. "Locality-Aware Channel-Wise Dropout for Occluded Face Recognition." IEEE transactions on image processing : a publication of the IEEE Signal Processing Society vol. 31 (2022): 788-798. doi: https://doi.org/10.1109/TIP.2021.3132827
He M, Zhang J, Shan S, Liu X, Wu Z, Chen X. Locality-Aware Channel-Wise Dropout for Occluded Face Recognition. IEEE Trans Image Process. 2022;31:788-798. doi: 10.1109/TIP.2021.3132827. Epub 2022 Jan 06. PMID: 34890329.
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De-Identification of Facial Features in Magnetic Resonance Images: Software Development Using Deep Learning Technology.

Journal of medical Internet research

Jeong YU, Yoo S, Kim YH, Shim WH.
PMID: 33208302
J Med Internet Res. 2020 Dec 10;22(12):e22739. doi: 10.2196/22739.

BACKGROUND: High-resolution medical images that include facial regions can be used to recognize the subject's face when reconstructing 3-dimensional (3D)-rendered images from 2-dimensional (2D) sequential images, which might constitute a risk of infringement of personal information when sharing data....

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Jeong YU, Yoo S, Kim YH, et al. De-Identification of Facial Features in Magnetic Resonance Images: Software Development Using Deep Learning Technology. J Med Internet Res. 2020;22(12):e22739doi: 10.2196/22739.
Jeong, Y. U., Yoo, S., Kim, Y. H., & Shim, W. H. (2020). De-Identification of Facial Features in Magnetic Resonance Images: Software Development Using Deep Learning Technology. Journal of medical Internet research, 22(12), e22739. https://doi.org/10.2196/22739
Jeong, Yeon Uk, et al. "De-Identification of Facial Features in Magnetic Resonance Images: Software Development Using Deep Learning Technology." Journal of medical Internet research vol. 22,12 (2020): e22739. doi: https://doi.org/10.2196/22739
Jeong YU, Yoo S, Kim YH, Shim WH. De-Identification of Facial Features in Magnetic Resonance Images: Software Development Using Deep Learning Technology. J Med Internet Res. 2020 Dec 10;22(12):e22739. doi: 10.2196/22739. PMID: 33208302; PMCID: PMC7759440.
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The engine of innovation with a human face - Prof. Ioannis Pallikaris.

Indian journal of ophthalmology

Kankariya V.
PMID: 33229637
Indian J Ophthalmol. 2020 Dec;68(12):2654-2655. doi: 10.4103/ijo.IJO_3287_20.

No abstract available.

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Kankariya V. The engine of innovation with a human face - Prof. Ioannis Pallikaris. Indian J Ophthalmol. 2020;68(12):2654-2655doi: 10.4103/ijo.IJO_3287_20.
Kankariya, V. (2020). The engine of innovation with a human face - Prof. Ioannis Pallikaris. Indian journal of ophthalmology, 68(12), 2654-2655. https://doi.org/10.4103/ijo.IJO_3287_20
Kankariya, Vardhaman. "The engine of innovation with a human face - Prof. Ioannis Pallikaris." Indian journal of ophthalmology vol. 68,12 (2020): 2654-2655. doi: https://doi.org/10.4103/ijo.IJO_3287_20
Kankariya V. The engine of innovation with a human face - Prof. Ioannis Pallikaris. Indian J Ophthalmol. 2020 Dec;68(12):2654-2655. doi: 10.4103/ijo.IJO_3287_20. PMID: 33229637; PMCID: PMC7856925.
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Detecting Facial Region and Landmarks at Once via Deep Network.

Sensors (Basel, Switzerland)

Kim T, Mok J, Lee E.
PMID: 34450804
Sensors (Basel). 2021 Aug 09;21(16). doi: 10.3390/s21165360.

For accurate and fast detection of facial landmarks, we propose a new facial landmark detection method. Previous facial landmark detection models generally perform a face detection step before landmark detection. This greatly affects landmark detection performance depending on which...

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Kim T, Mok J, Lee E. Detecting Facial Region and Landmarks at Once via Deep Network. Sensors (Basel). 2021;21(16)doi: 10.3390/s21165360.
Kim, T., Mok, J., & Lee, E. (2021). Detecting Facial Region and Landmarks at Once via Deep Network. Sensors (Basel, Switzerland), 21(16), . https://doi.org/10.3390/s21165360
Kim, Taehyung, et al. "Detecting Facial Region and Landmarks at Once via Deep Network." Sensors (Basel, Switzerland) vol. 21,16 (2021). doi: https://doi.org/10.3390/s21165360
Kim T, Mok J, Lee E. Detecting Facial Region and Landmarks at Once via Deep Network. Sensors (Basel). 2021 Aug 09;21(16). doi: 10.3390/s21165360. PMID: 34450804; PMCID: PMC8401714.
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Showing 205 to 210 of 210 entries