Search Results for author: Guoqing Li

Found 12 papers, 2 papers with code

Boosting Tail Neural Network for Realtime Custom Keyword Spotting

no code implementations24 May 2022 Sihao Xue, Qianyao Shen, Guoqing Li

In this paper, we propose a Boosting Tail Neural Network (BTNN) for improving the performance of Realtime Custom Keyword Spotting (RCKS) that is still an industrial challenge for demanding powerful classification ability with limited computation resources.

Keyword Spotting

Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots

1 code implementation CVPR 2022 Zejin Wang, Jiazheng Liu, Guoqing Li, Hua Han

Self-supervised denoisers, which learn only from single noisy images, solve the data collection problem.

Image Denoising

Optimal Scheduling of Integrated Demand Response-Enabled Community Integrated Energy Systems in Uncertain Environments

no code implementations18 Aug 2021 Yang Li, Bin Wang, Zhen Yang, Jiazheng Li, Guoqing Li

The community integrated energy system (CIES) is an essential energy internet carrier that has recently been the focus of much attention.

Scheduling

Coordinating Flexible Demand Response and Renewable Uncertainties for Scheduling of Community Integrated Energy Systems with an Electric Vehicle Charging Station: A Bi-level Approach

no code implementations16 Jul 2021 Yang Li, Meng Han, Zhen Yang, Guoqing Li

A community integrated energy system (CIES) with an electric vehicle charging station (EVCS) provides a new way for tackling growing concerns of energy efficiency and environmental pollution, it is a critical task to coordinate flexible demand response and multiple renewable uncertainties.

Scheduling

Optimal Scheduling of Integrated Demand Response-Enabled Integrated Energy Systems with Uncertain Renewable Generations: A Stackelberg Game Approach

no code implementations8 Mar 2021 Yang Li, Chunling Wang, Guoqing Li, Chen Chen

In order to balance the interests of integrated energy operator (IEO) and users, a novel Stackelberg game-based optimization framework is proposed for the optimal scheduling of integrated demand response (IDR)-enabled integrated energy systems with uncertain renewable generations, where the IEO acts as the leader who pursues the maximization of his profits by setting energy prices, while the users are the follower who adjusts energy consumption plans to minimize their energy costs.

Scheduling

Neural Relational Inference with Efficient Message Passing Mechanisms

1 code implementation23 Jan 2021 Siyuan Chen, Jiahai Wang, Guoqing Li

Additionally, the structural prior knowledge, symmetry as a special case, is introduced for better relation prediction in more complex systems.

Relation

Temporal Spatial-Adaptive Interpolation with Deformable Refinement for Electron Microscopic Images

no code implementations17 Jan 2021 Zejin Wang, Guodong Sun, Lina Zhang, Guoqing Li, Hua Han

The TSA interpolation module aggregates temporal contexts and then adaptively samples the spatial-related features with the proposed residual spatial adaptive block.

Optical Flow Estimation Video Frame Interpolation

DAN: A Deformation-Aware Network for Consecutive Biomedical Image Interpolation

no code implementations23 Apr 2020 Zejin Wang, Guoqing Li, Xi Chen, Hua Han

The continuity of biological tissue between consecutive biomedical images makes it possible for the video interpolation algorithm, to recover large area defects and tears that are common in biomedical images.

PSDNet and DPDNet: Efficient channel expansion, Depthwise-Pointwise-Depthwise Inverted Bottleneck Block

no code implementations3 Sep 2019 Guoqing Li, Meng Zhang, Qianru Zhang, Ziyang Chen, Wenzhao Liu, Jiaojie Li, Xuzhao Shen, Jianjun Li, Zhenyu Zhu, Chau Yuen

To design more efficient lightweight concolutional neural netwok, Depthwise-Pointwise-Depthwise inverted bottleneck block (DPD block) is proposed and DPDNet is designed by stacking DPD block.

GUN: Gradual Upsampling Network for Single Image Super-Resolution

no code implementations13 Mar 2017 Yang Zhao, Guoqing Li, Wenjun Xie, Wei Jia, Hai Min, Xiaoping Liu

The GUN consists of an input layer, multiple upsampling and convolutional layers, and an output layer.

Image Super-Resolution

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