Search Results for author:
Found 12 papers, 6 papers with code
Hybrid HMM Decoder For Convolutional Codes By Joint Trellis-Like Structure and Channel Prior
In this paper, we propose the use of a Hidden Markov Model (HMM) for the reconstruction of convolutional codes and decoding by the Viterbi algorithm.
IDLat: An Importance-Driven Latent Generation Method for Scientific Data
We qualitatively and quantitatively evaluate the effectiveness and efficiency of latent representations generated by our method with data from multiple scientific visualization applications.
VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations
In the model inference stage, we predict the latent representations at previously selected viewpoints and decode the latent representations to data space.
Joint Noise Reduction and Listening Enhancement for Full-End Speech Enhancement
Speech enhancement (SE) methods mainly focus on recovering clean speech from noisy input.
DDS: A new device-degraded speech dataset for speech enhancement
A large and growing amount of speech content in real-life scenarios is being recorded on consumer-grade devices in uncontrolled environments, resulting in degraded speech quality.
Local Latent Representation based on Geometric Convolution for Particle Data Feature Exploration
Feature related particle data analysis plays an important role in many scientific applications such as fluid simulations, cosmology simulations and molecular dynamics.
Multi-Metric Optimization using Generative Adversarial Networks for Near-End Speech Intelligibility Enhancement
The intelligibility of speech severely degrades in the presence of environmental noise and reverberation.
Noise Tokens: Learning Neural Noise Templates for Environment-Aware Speech Enhancement
In recent years, speech enhancement (SE) has achieved impressive progress with the success of deep neural networks (DNNs).
Audio and Speech Processing
iMetricGAN: Intelligibility Enhancement for Speech-in-Noise using Generative Adversarial Network-based Metric Learning
The intelligibility of natural speech is seriously degraded when exposed to adverse noisy environments.
Audio and Speech Processing Sound
NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation
We utilize the trained network to perform interactive parameter sensitivity analysis of the original simulation at multiple levels-of-detail as well as recommend optimal parameter configurations using the activation maximization framework of neural networks.
Faster super-resolution imaging with auto-correlation two-step deconvolution
Despite super-resolution fluorescence blinking microscopes break the diffraction limit, the intense phototoxic illumination and long-term image sequences thus far still pose to major challenges in visualizing live-organisms.
Optics
Volumetric Light-field Encryption at the Microscopic Scale
We report a light-field based method that allows the optical encryption of three-dimensional (3D) volumetric information at the microscopic scale in a single 2D light-field image.
