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Found 12 papers, 0 papers with code
EEG decoding with conditional identification information
Decoding EEG signals is crucial for unraveling human brain and advancing brain-computer interfaces.
Delayed Memory Unit: Modelling Temporal Dependency Through Delay Gate
Recurrent Neural Networks (RNNs) are renowned for their adeptness in modeling temporal dependencies, a trait that has driven their widespread adoption for sequential data processing.
Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition
Spiking neural networks (SNN) are a promising research avenue for building accurate and efficient automatic speech recognition systems.
Ranked #2 on
Audio Classification
on SHD
Spikemax: Spike-based Loss Methods for Classification
In addition, we demonstrate state of the art performances on these datasets, achieving faster inference speed and less energy consumption.
Axonal Delay As a Short-Term Memory for Feed Forward Deep Spiking Neural Networks
The information of spiking neural networks (SNNs) are propagated between the adjacent biological neuron by spikes, which provides a computing paradigm with the promise of simulating the human brain.
GAMnet: Robust Feature Matching via Graph Adversarial-Matching Network
Also, GAMnet exploits sparse GM optimization as correspondence solver which is differentiable and can also incorporate discrete one-to-one matching constraints approximately in natural in the final matching prediction.
Ranked #7 on
Graph Matching
on PASCAL VOC
(matching accuracy metric)
NTIRE 2021 Challenge on Perceptual Image Quality Assessment
This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2021.
GLMNet: Graph Learning-Matching Networks for Feature Matching
However, the matching graphs we feed to existing graph convolutional matching networks are generally fixed and independent of graph matching, which thus are not guaranteed to be optimal for the graph matching task.
Ranked #15 on
Graph Matching
on Willow Object Class
Brain2Char: A Deep Architecture for Decoding Text from Brain Recordings
These results set a new state-of-the-art on decoding text from brain and demonstrate the potential of Brain2Char as a high-performance communication BCI.
Modeling neural dynamics during speech production using a state space variational autoencoder
Characterizing the neural encoding of behavior remains a challenging task in many research areas due in part to complex and noisy spatiotemporal dynamics of evoked brain activity.
Neural networks based EEG-Speech Models
In this paper, we propose an end-to-end neural network (NN) based EEG-speech (NES) modeling framework, in which three network structures are developed to map imagined EEG signals to phonemes.
Enhanced Factored Three-Way Restricted Boltzmann Machines for Speech Detection
In this letter, we propose enhanced factored three way restricted Boltzmann machines (EFTW-RBMs) for speech detection.
