Results 61 to 70 of about 220,848 (275)

Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition

, 2019
In the recent year, state-of-the-art for facial micro-expression recognition have been significantly advanced by deep neural networks. The robustness of deep learning has yielded promising performance beyond that of traditional handcrafted approaches ...
Gan, Y. S., Huang, Yen-Chang, Khor, Huai-Qian, Liong, Sze-Teng, See, John   +4 more
core   +1 more source

Optical neural stimulation modeling on degenerative neocortical neural networks [PDF]

SPIE Proceedings, 2015
This work has been partially supported by the project MAT2012-38664-C02-01 of the Spanish Ministry of Economy and Competitiveness, and by San Cándido Foundation.
Zverev, Mihail, Fanjul Vélez, Félix||, Salas García, Irene, Arce Diego, José Luis   +3 more
openaire   +2 more sources

Super‐Refractory Status Epilepticus (SRSE) in a Patient With Compound Heterozygous OPA1 Variants: Case Report and Literature Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi, Lara Basovic, Christopher Michael McGraw   +2 more
wiley   +1 more source

Advancements in Optical Diffraction Neural Networks

Photonics
Optical diffraction neural networks (ODNNs) represent a promising advancement in computational optics, with significant potential for applications in image classification, image reconstruction, and biomedical imaging.
Tianyu Han, Jiawei Sun, Xibin Yang
doaj   +1 more source

Spiking Optical Patterns and Synchronization

, 2007
We analyze the time resolved spike statistics of a solitary and two mutually interacting chaotic semiconductor lasers whose chaos is characterized by apparently random, short intensity spikes.
Aviad, Yaara, Cohen, Elad, Kanter, Ido, Khaykovich, Lev, Kinzel, Wolfgang, Kopelowitz, Evi, Rosenbluh, Michael, Yoskovits, Pinhas   +7 more
core   +1 more source

Diffusion Spectrum Imaging Maps Early Axonal Loss and a Unique Progressive Signal in Neuronal Intranuclear Inclusion Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To delineate specific in vivo white matter pathology in neuronal intranuclear inclusion disease (NIID) using diffusion spectrum imaging (DSI) and define its clinical relevance. Methods DSI was performed on 42 NIID patients and 38 matched controls.
Kaiyan Jiang, Yixiu Pei, Xiaobao Hu, Ying Xiong, Fang Wang, Yanyan Yu, Min Zhu, Dandan Tan, Meihong Zhou, Daojun Hong, Fuqing Zhou   +10 more
wiley   +1 more source

Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende, Emilien Petit, Young Woo Park, Sophie Tezenas du Montcel, James M. Joers, Jonathan M. DuBois, H. Moore Arnold, Michal Povazan, Ipek Özdemir, Guita Banan, Romain Valabregue, Philipp Ehses, Jennifer Faber, Chiadi U. Onyike, Peter B. Barker, Jeremy D. Schmahmann, Eva‐Maria Ratai, Sub H. Subramony, Thomas H. Mareci, Khalaf O. Bushara, Henry Paulson, Thomas Klockgether, Alexandra Durr, Tetsuo Ashizawa, Christophe Lenglet, Gülin Öz, READISCA Investigators   +26 more
wiley   +1 more source

A machine learning approach to the prediction of the dispersion property of oxide glass

AIP Advances, 2021
In this study, we built a model for predicting the optical dispersion property of oxide glasses via machine-learning techniques such as kernel ridge regression, neural networks, and random forests.
Yomei Tokuda, Misa Fujisawa, Jinto Ogawa, Yoshikatsu Ueda   +3 more
doaj   +1 more source

Structure–Function Decoupling of the Sensorimotor and Default Mode Networks in Black Americans With MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Multiple sclerosis (MS) exhibits racially disparate rates of disease progression. Black people with MS (B‐PwMS) experience a more severe disease course than non‐Hispanic White people with MS (NHW‐PwMS). Here we investigated structural and functional connectivity as well as structure–function decoupling in the ...
Emilio Cipriano, Giacomo Boffa, Maria Petracca, Marta Ponzano, Nicole Graziano, Claire Wigley, Claire Riley, Jonathan Howard, Pietro Bontempi, Sylvia Klineova, Fred Lublin, Matilde Inglese   +11 more
wiley   +1 more source

All-optical nonlinear activation function based on stimulated Brillouin scattering

Nanophotonics
Optical neural networks have demonstrated their potential to overcome the computational bottleneck of modern digital electronics. However, their development towards high-performing computing alternatives is hindered by one of the optical neural networks’
Slinkov Grigorii, Becker Steven, Englund Dirk, Stiller Birgit   +3 more
doaj   +1 more source