Search Results for author: Haoyu Li

Found 12 papers, 6 papers with code

Hybrid HMM Decoder For Convolutional Codes By Joint Trellis-Like Structure and Channel Prior

1 code implementation26 Oct 2022 Haoyu Li, Xuan Wang, Tong Liu, Dingyi Fang, Baoying Liu

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

no code implementations5 Aug 2022 Jingyi Shen, Haoyu Li, Jiayi Xu, Ayan Biswas, Han-Wei Shen

We qualitatively and quantitatively evaluate the effectiveness and efficiency of latent representations generated by our method with data from multiple scientific visualization applications.

Data Visualization

VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations

1 code implementation25 Jul 2022 Neng Shi, Jiayi Xu, Haoyu Li, Hanqi Guo, Jonathan Woodring, Han-Wei Shen

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

no code implementations22 Mar 2022 Haoyu Li, Yun Liu, Junichi Yamagishi

Speech enhancement (SE) methods mainly focus on recovering clean speech from noisy input.

Speech Enhancement

DDS: A new device-degraded speech dataset for speech enhancement

no code implementations16 Sep 2021 Haoyu Li, Junichi Yamagishi

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.

Speech Enhancement

Local Latent Representation based on Geometric Convolution for Particle Data Feature Exploration

1 code implementation27 May 2021 Haoyu Li, Han-Wei Shen

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

1 code implementation17 Apr 2021 Haoyu Li, Junichi Yamagishi

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

no code implementations8 Apr 2020 Haoyu Li, Junichi Yamagishi

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

1 code implementation Interspeech 2020 Haoyu Li, Szu-Wei Fu, Yu Tsao, Junichi Yamagishi

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

no code implementations19 Apr 2019 Subhashis Hazarika, Haoyu Li, Ko-Chih Wang, Han-Wei Shen, Ching-Shan Chou

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

2 code implementations19 Sep 2018 Weisong Zhao, Jian Liu, Chenqi Kong, Yixuan Zhao, Changliang Guo, Chen-Guang Liu, Xiangyan Ding, Xumin Ding, Jiubin Tan, Haoyu Li

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.


Volumetric Light-field Encryption at the Microscopic Scale

no code implementations26 Oct 2016 Haoyu Li, Changliang Guo, Inbarasan Muniraj, Bryce C. Schroeder, John T. Sheridan, Shu Jia

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.

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