Hui Li

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Xiamen University ∙ Purdue University ∙ Beijing Normal University ∙ Harbin Institute of Technology ∙ The University of Hong Kong ∙ Xidian University ∙ NetEase, Inc

Graduate Research Assistant at The University of Hong Kong since 2013, PhD in Department of Computer Science at The University of Hong Kong, PhD Intern at Systems and Machine Learning group, NEC Laboratories Europe 2017

Multi-focus Image Fusion Based on Similarity Characteristics

A novel multi-focus image fusion algorithm performed in spatial domain b...
12/17/2019 ∙ by Ya-Qiong Zhang, et al. ∙ 22 ∙ share

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Machine-learning-based methods for output only structural modal identification

In this study, we propose a machine-learning-based approach to identify ...
04/16/2020 ∙ by Yuequan Bao, et al. ∙ 15 ∙ share

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Automatic trajectory measurement of large numbers of crowded objects

Complex motion patterns of natural systems, such as fish schools, bird f...
02/03/2019 ∙ by Hui Li, et al. ∙ 12 ∙ share

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Underwater image enhancement with Image Colorfulness Measure

Due to the absorption and scattering effects of the water, underwater im...
04/18/2020 ∙ by Hui Li, et al. ∙ 11 ∙ share

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Intention Propagation for Multi-agent Reinforcement Learning

A hallmark of an AI agent is to mimic human beings to understand and int...
04/19/2020 ∙ by Chao Qu, et al. ∙ 11 ∙ share

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Infrared and visible image fusion using a novel deep decomposition method

Infrared and visible image fusion is an important problem in image fusio...
11/06/2018 ∙ by Hui Li, et al. ∙ 8 ∙ share

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Single-shot 3D shape reconstruction using deep convolutional neural networks

A robust single-shot 3D shape reconstruction technique integrating the f...
09/17/2019 ∙ by Hieu Nguyen, et al. ∙ 5 ∙ share

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Visual Question Answering as Reading Comprehension

Visual question answering (VQA) demands simultaneous comprehension of bo...
11/29/2018 ∙ by Hui Li, et al. ∙ 4 ∙ share

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Learning Structural Graph Layouts and 3D Shapes for Long Span Bridges 3D Reconstruction

A learning-based 3D reconstruction method for long-span bridges is propo...
07/08/2019 ∙ by Fangqiao Hu, et al. ∙ 3 ∙ share

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Multi-focus Noisy Image Fusion using Low-Rank Representation

In the process of image acquisition, the noise is inevitable for source ...
04/25/2018 ∙ by Hui Li, et al. ∙ 2 ∙ share

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Infrared and Visible Image Fusion with ResNet and zero-phase component analysis

In image fusion task, feature extraction and processing are keys for fus...
06/19/2018 ∙ by Hui Li, et al. ∙ 2 ∙ share

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Towards End-to-End Text Spotting in Natural Scenes

Text spotting in natural scene images is of great importance for many im...
06/14/2019 ∙ by Hui Li, et al. ∙ 1 ∙ share

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Push and Pull Search for Solving Constrained Multi-objective Optimization Problems

This paper proposes a push and pull search (PPS) framework for solving c...
09/15/2017 ∙ by Zhun Fan, et al. ∙ 0 ∙ share

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Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks

In this work, we tackle the problem of car license plate detection and r...
09/26/2017 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Difficulty Adjustable and Scalable Constrained Multi-objective Test Problem Toolkit

Multi-objective evolutionary algorithms (MOEAs) have achieved great prog...
12/21/2016 ∙ by Zhun Fan, et al. ∙ 0 ∙ share

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Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks

In this work, we jointly address the problem of text detection and recog...
07/13/2017 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Bayesian System Identification based on Hierarchical Sparse Bayesian Learning and Gibbs Sampling with Application to Structural Damage Assessment

The focus in this paper is Bayesian system identification based on noisy...
01/13/2017 ∙ by Yong Huang, et al. ∙ 0 ∙ share

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Improved phase-unwrapping method using geometric constraints

Conventional dual-frequency fringe projection algorithm often suffers fr...
09/28/2016 ∙ by Guangliang Du, et al. ∙ 0 ∙ share

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Enhanced high dynamic range 3D shape measurement based on generalized phase-shifting algorithm

It is a challenge for Phase Measurement Profilometry (PMP) to measure ob...
06/07/2016 ∙ by Minmin Wang, et al. ∙ 0 ∙ share

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Robust Bayesian compressive sensing with data loss recovery for structural health monitoring signals

The application of compressive sensing (CS) to structural health monitor...
03/28/2015 ∙ by Yong Huang, et al. ∙ 0 ∙ share

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Reading Car License Plates Using Deep Convolutional Neural Networks and LSTMs

In this work, we tackle the problem of car license plate detection and r...
01/21/2016 ∙ by Hui Li, et al. ∙ 0 ∙ share

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KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization

We consider the image classification problem via kernel collaborative re...
10/17/2014 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Dictionary learning based image enhancement for rarity detection

Image enhancement is an important image processing technique that proces...
05/04/2013 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Time is What Prevents Everything from Happening at Once: Propagation Time-conscious Influence Maximization

The influence maximization (IM) problem as defined in the seminal paper ...
05/31/2017 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Optimize transfer learning for lung diseases in bronchoscopy using a new concept: sequential fine-tuning

Bronchoscopy inspection as a follow-up procedure from the radiological i...
02/10/2018 ∙ by Tao Tan, et al. ∙ 0 ∙ share

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A Unified Form of EVENODD and RDP Codes and Their Efficient Decoding

Array codes have been widely employed in storage systems, such as Redund...
03/09/2018 ∙ by Hanxu Hou, et al. ∙ 0 ∙ share

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TransRev: Modeling Reviews as Translations from Users to Items

The text of a review expresses the sentiment a customer has towards a pa...
01/30/2018 ∙ by Alberto García-Durán, et al. ∙ 0 ∙ share

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Real-world Noisy Image Denoising: A New Benchmark

Most of previous image denoising methods focus on additive white Gaussia...
04/07/2018 ∙ by Jun Xu, et al. ∙ 0 ∙ share

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Infrared and Visible Image Fusion using a Deep Learning Framework

In recent years, deep learning has become a very active research tool wh...
04/19/2018 ∙ by Hui Li, et al. ∙ 0 ∙ share

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DenseFuse: A Fusion Approach to Infrared and Visible Images

In this paper, we present a novel deep learning architecture for infrare...
04/23/2018 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Multi-focus Image Fusion using dictionary learning and Low-Rank Representation

Among the representation learning, the low-rank representation (LRR) is ...
04/23/2018 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Infrared and visible image fusion using Latent Low-Rank Representation

Infrared and visible image fusion is an important problem in the field o...
04/24/2018 ∙ by Hui Li, et al. ∙ 0 ∙ share

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General solutions for nonlinear differential equations: a deep reinforcement learning approach

Physicists use differential equations to describe the physical dynamical...
05/13/2018 ∙ by Shiyin Wei, et al. ∙ 0 ∙ share

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Adversarial Attack on Graph Structured Data

Deep learning on graph structures has shown exciting results in various ...
06/06/2018 ∙ by Hanjun Dai, et al. ∙ 0 ∙ share

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ONCE and ONCE+: Counting the Frequency of Time-constrained Serial Episodes in a Streaming Sequence

As a representative sequential pattern mining problem, counting the freq...
01/29/2018 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Estimation of marginal model with subgroup auxiliary information

Marginal model is a popular instrument for studying longitudinal data an...
06/08/2018 ∙ by Jie He, et al. ∙ 0 ∙ share

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LRMM: Learning to Recommend with Missing Modalities

Multimodal learning has shown promising performance in content-based rec...
08/21/2018 ∙ by Cheng Wang, et al. ∙ 0 ∙ share

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On the Duality and File Size Hierarchy of Fractional Repetition Codes

Distributed storage systems that deploy erasure codes can provide better...
08/06/2018 ∙ by Bing Zhu, et al. ∙ 0 ∙ share

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Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition

Recognizing irregular text in natural scene images is challenging due to...
11/02/2018 ∙ by Hui Li, et al. ∙ 0 ∙ share

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A LQD-RKHS-based distribution-to-distribution regression method and its application to restore distributions of missing SHM data

Data loss is a critical problem in structural health monitoring (SHM). P...
11/21/2018 ∙ by Zhicheng Chen, et al. ∙ 0 ∙ share

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Automatically Generate Steganographic Text Based on Markov Model and Huffman Coding

Steganography, as one of the three basic information security systems, h...
11/12/2018 ∙ by Zhongliang Yang, et al. ∙ 0 ∙ share

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Compressive-Sensing Data Reconstruction for Structural Health Monitoring: A Machine-Learning Approach

Compressive sensing (CS) has been studied and applied in structural heal...
01/07/2019 ∙ by Yuequan Bao, et al. ∙ 0 ∙ share

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The Crossover-Distance for ISI-Correcting Decoding of Convolutional Codes in Diffusion-Based Molecular Communications

In diffusion based molecular communication, the intersymbol interference...
12/29/2018 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Double Neural Counterfactual Regret Minimization

Counterfactual Regret Minimization (CRF) is a fundamental and effective ...
12/27/2018 ∙ by Hui Li, et al. ∙ 0 ∙ share

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LQD-RKHS-based distribution-to-distribution regression methodology for restoring the probability distributions of missing SHM data

Data loss is a critical problem in structural health monitoring (SHM). P...
11/21/2018 ∙ by Zhicheng Chen, et al. ∙ 0 ∙ share

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Neural Model-Based Reinforcement Learning for Recommendation

There are great interests as well as many challenges in applying reinfor...
12/27/2018 ∙ by Xinshi Chen, et al. ∙ 0 ∙ share

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Pedestrian re-identification based on Tree branch network with local and global learning

Deep part-based methods in recent literature have revealed the great pot...
03/31/2019 ∙ by Hui Li, et al. ∙ 0 ∙ share

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A Simple and Robust Convolutional-Attention Network for Irregular Text Recognition

Reading irregular text of arbitrary shape in natural scene images is sti...
04/02/2019 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems

Data sparsity and data imbalance are practical and challenging issues in...
03/26/2019 ∙ by Cheng Wang, et al. ∙ 0 ∙ share

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MMKG: Multi-Modal Knowledge Graphs

We present MMKG, a collection of three knowledge graphs that contain bot...
03/13/2019 ∙ by Ye Liu, et al. ∙ 0 ∙ share

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Hui Li

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