Results 11 to 20 of about 151,868 (248)
How major depressive disorder affects the ability to decode multimodal dynamic emotional stimuli [PDF]
, 2016 Most studies investigating the processing of emotions in depressed patients reported impairments in the decoding of negative emotions. However, these studies adopted static stimuli (mostly stereotypical facial expressions corresponding to basic emotions)
Esposito, Anna +4 more
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Unsupervised decoding of long-term, naturalistic human neural recordings with automated video and audio annotations [PDF]
, 2015 Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing.
Brunton, Bingni W. +4 more
core +3 more sources
Frontiers in Computational Neuroscience, 2022 A crucial point in neuroscience is how to correctly decode cognitive information from brain dynamics for motion control and neural rehabilitation.
Haitao Yu +5 more
doaj +1 more source
MEG Decoding Across Subjects [PDF]
, 2014 Brain decoding is a data analysis paradigm for neuroimaging experiments that is based on predicting the stimulus presented to the subject from the concurrent brain activity.
Avesani, Paolo +2 more
core +1 more source
Frontiers in Neuroscience, 2022 ObjectiveMulti-frequency steady-state visual evoked potential (SSVEP) stimulation and decoding methods enable the representation of a large number of visual targets in brain-computer interfaces (BCIs).
Jing Mu +6 more
doaj +1 more source
AMR Dependency Parsing with a Typed Semantic Algebra
, 2018 We present a semantic parser for Abstract Meaning Representations which learns to parse strings into tree representations of the compositional structure of an AMR graph.
Fowlie, Meaghan +4 more
core +1 more source
A Convolutional Encoder Model for Neural Machine Translation
, 2017 The prevalent approach to neural machine translation relies on bi-directional LSTMs to encode the source sentence. In this paper we present a faster and simpler architecture based on a succession of convolutional layers.
Auli, Michael +3 more
core +1 more source
Effective Inference for Generative Neural Parsing
, 2017 Generative neural models have recently achieved state-of-the-art results for constituency parsing. However, without a feasible search procedure, their use has so far been limited to reranking the output of external parsers in which decoding is more ...
Fried, Daniel +2 more
core +1 more source
IEEE Transactions on Neural Systems and Rehabilitation EngineeringMotor imagery brain-computer interface (MI-BCI) based on non-invasive electroencephalogram (EEG) signals is a typical paradigm of BCI. However, existing decoding methods face significant challenges in terms of signal decoding accuracy, real-time ...
Sixiong Ke +5 more
doaj +1 more source
Multi-Scale Convolutional Network for Space-Based ADS-B Signal Separation with Single Antenna
Applied Sciences, 2022 Automatic Dependent Surveillance-Broadcast (ADS-B) signals are very vital in air traffic control. However, the space-based ADS-B signals are easily overlapped and their message cannot be correctly received.
Yan Bi, Chuankun Li
doaj +1 more source