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Found 8 papers, 3 papers with code
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 common consumer devices in uncontrolled environments, resulting in degraded speech quality.
Time Varying Particle Data Feature Extraction and Tracking with Neural Networks
In this paper, we take a deep learning approach to create feature representations for scientific particle data to assist feature extraction and tracking.
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.