Search Results for author: Rui Li

Found 87 papers, 29 papers with code

Treasures Outside Contexts: Improving Event Detection via Global Statistics

1 code implementation EMNLP 2021 Rui Li, Wenlin Zhao, Cheng Yang, Sen Su

Event detection (ED) aims at identifying event instances of specified types in given texts, which has been formalized as a sequence labeling task.

Event Detection

Sparse Covariance Modeling in High Dimensions with Gaussian Processes

no code implementations NeurIPS 2018 Rui Li, Kishan Kc, Feng Cui, Justin Domke, Anne Haake

This paper studies statistical relationships among components of high-dimensional observations varying across non-random covariates.

Gaussian Processes

Reflection Separation via Multi-bounce Polarization State Tracing

no code implementations ECCV 2020 Rui Li, Simeng Qiu, Guangming Zang, Wolfgang Heidrich

Through a combination of a new polarization-guided image formation model and a novel supervised learning framework for the interpretation of a ray-tracing polarized image formation model, a general method is obtained to tackle general image reflection removal problems.

Reflection Removal

Predicting Biomedical Interactions with Probabilistic Model Selection for Graph Neural Networks

no code implementations22 Nov 2022 Kishan K C, Rui Li, Paribesh Regmi, Anne R. Haake

Experiments on four interaction datasets show that our proposed method achieves accurate and calibrated predictions.

Model Selection

Towards Improved Learning in Gaussian Processes: The Best of Two Worlds

no code implementations11 Nov 2022 Rui Li, ST John, Arno Solin

Gaussian process training decomposes into inference of the (approximate) posterior and learning of the hyperparameters.

Gaussian Processes Hyperparameter Optimization +1

Learning on Large-scale Text-attributed Graphs via Variational Inference

2 code implementations26 Oct 2022 Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang

In this paper, we propose an efficient and effective solution to learning on large text-attributed graphs by fusing graph structure and language learning with a variational Expectation-Maximization (EM) framework, called GLEM.

Variational Inference

The Future of Consumer Edge-AI Computing

no code implementations19 Oct 2022 Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane

Deep Learning has proliferated dramatically across consumer devices in less than a decade, but has been largely powered through the hardware acceleration within isolated devices.

Test-Time Training for Graph Neural Networks

no code implementations17 Oct 2022 Yiqi Wang, Chaozhuo Li, Wei Jin, Rui Li, Jianan Zhao, Jiliang Tang, Xing Xie

To bridge such gap, in this work we introduce the first test-time training framework for GNNs to enhance the model generalization capacity for the graph classification task.

Graph Classification Self-Supervised Learning

Spatial-then-Temporal Self-Supervised Learning for Video Correspondence

no code implementations16 Sep 2022 Rui Li, Dong Liu

Specifically, we firstly extract spatial features from unlabeled images via contrastive learning, and secondly enhance the features by exploiting the temporal cues in unlabeled videos via reconstructive learning.

Contrastive Learning Self-Supervised Learning

TFusion: Transformer based N-to-One Multimodal Fusion Block

no code implementations26 Aug 2022 Zecheng Liu, Jia Wei, Rui Li

In this work, we apply TFusion to different backbone networks for multimodal human activity recognition and brain tumor segmentation tasks.

Brain Tumor Segmentation Human Activity Recognition +1

Learning Multi-Modal Brain Tumor Segmentation from Privileged Semi-Paired MRI Images with Curriculum Disentanglement Learning

no code implementations26 Aug 2022 Zecheng Liu, Jia Wei, Rui Li

Specifically, in the first step, we propose to conduct reconstruction and segmentation with augmented intra-modality style-consistent images.

Brain Tumor Segmentation Disentanglement +2

A Sahlqvist-style Correspondence Theorem for Linear-time Temporal Logic

no code implementations13 Jun 2022 Rui Li, Francesco Belardinelli

The main result of this paper is to prove the correspondence of LTL Sahlqvist formulas to frame conditions that are definable in first-order language.

A Look at Improving Robustness in Visual-inertial SLAM by Moment Matching

no code implementations27 May 2022 Arno Solin, Rui Li, Andrea Pilzer

The fusion of camera sensor and inertial data is a leading method for ego-motion tracking in autonomous and smart devices.

Unsupervised Multi-Modal Medical Image Registration via Discriminator-Free Image-to-Image Translation

1 code implementation28 Apr 2022 Zekang Chen, Jia Wei, Rui Li

In this paper, we propose a novel translation-based unsupervised deformable image registration approach to convert the multi-modal registration problem to a mono-modal one.

Computed Tomography (CT) Image Registration +3

HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images

no code implementations14 Apr 2022 Jikuan Qian, Rui Li, Xin Yang, Yuhao Huang, Mingyuan Luo, Zehui Lin, Wenhui Hong, Ruobing Huang, Haining Fan, Dong Ni, Jun Cheng

The hybrid framework consists of a pre-trained backbone and several searched cells (i. e., network building blocks), which takes advantage of the strengths of both NAS and the expert knowledge from existing convolutional neural networks.

Image Classification Neural Architecture Search

Slice Imputation: Intermediate Slice Interpolation for Anisotropic 3D Medical Image Segmentation

no code implementations21 Mar 2022 Zhaotao Wu, Jia Wei, Jiabing Wang, Rui Li

We introduce a novel frame-interpolation-based method for slice imputation to improve segmentation accuracy for anisotropic 3D medical images, in which the number of slices and their corresponding segmentation labels can be increased between two consecutive slices in anisotropic 3D medical volumes.

Image Segmentation Imputation +2

Neural Adaptive SCEne Tracing

no code implementations28 Feb 2022 Rui Li, Darius Rückert, Yuanhao Wang, Ramzi Idoughi, Wolfgang Heidrich

Neural rendering with implicit neural networks has recently emerged as an attractive proposition for scene reconstruction, achieving excellent quality albeit at high computational cost.

Neural Rendering

HousE: Knowledge Graph Embedding with Householder Parameterization

1 code implementation16 Feb 2022 Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang

The effectiveness of knowledge graph embedding (KGE) largely depends on the ability to model intrinsic relation patterns and mapping properties.

Knowledge Graph Embedding Relation Mapping

NeAT: Neural Adaptive Tomography

no code implementations4 Feb 2022 Darius Rückert, Yuanhao Wang, Rui Li, Ramzi Idoughi, Wolfgang Heidrich

Through a combination of neural features with an adaptive explicit representation, we achieve reconstruction times far superior to existing neural inverse rendering methods.

3D Reconstruction Neural Rendering

Dilated Continuous Random Field for Semantic Segmentation

1 code implementation1 Feb 2022 Xi Mo, Xiangyu Chen, Cuncong Zhong, Rui Li, Kaidong Li, Usman Sajid

Mean field approximation methodology has laid the foundation of modern Continuous Random Field (CRF) based solutions for the refinement of semantic segmentation.

Semantic Segmentation

Motion-Focused Contrastive Learning of Video Representations

1 code implementation ICCV 2021 Rui Li, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Dong Liu, Tao Mei

To this end, we compose a duet of exploiting the motion for data augmentation and feature learning in the regime of contrastive learning.

Contrastive Learning Data Augmentation +2

A New Perspective on the Effects of Spectrum in Graph Neural Networks

1 code implementation14 Dec 2021 Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, BaoCai Yin

Many improvements on GNNs can be deemed as operations on the spectrum of the underlying graph matrix, which motivates us to directly study the characteristics of the spectrum and their effects on GNN performance.

Graph Classification Graph Property Prediction +1

Building extraction with vision transformer

no code implementations29 Nov 2021 Libo Wang, Shenghui Fang, Rui Li, Xiaoliang Meng

Second, spatial details are not sufficiently preserved during the feature extraction of the Vision Transformer, resulting in the inability for fine-grained building segmentation.

Image Classification Object Detection +1

Joint Inference for Neural Network Depth and Dropout Regularization

2 code implementations NeurIPS 2021 Kishan K C, Rui Li, MohammadMahdi Gilany

We propose a unified Bayesian model selection method to jointly infer the most plausible network depth warranted by data, and perform dropout regularization simultaneously.

Continual Learning Model Selection

Shape and Reflectance Reconstruction in Uncontrolled Environments by Differentiable Rendering

no code implementations25 Oct 2021 Rui Li, Guangmin Zang, Miao Qi, Wolfgang Heidrich

Simultaneous reconstruction of geometry and reflectance properties in uncontrolled environments remains a challenging problem.

Novel View Synthesis

A Channel Coding Benchmark for Meta-Learning

1 code implementation15 Jul 2021 Rui Li, Ondrej Bohdal, Rajesh Mishra, Hyeji Kim, Da Li, Nicholas Lane, Timothy Hospedales

We use our MetaCC benchmark to study several aspects of meta-learning, including the impact of task distribution breadth and shift, which can be controlled in the coding problem.


Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images

1 code implementation23 Jun 2021 Libo Wang, Rui Li, Dongzhi Wang, Chenxi Duan, Teng Wang, Xiaoliang Meng

Specifically, the dependency path is conducted based on the ResT, a novel Transformer backbone with memory-efficient multi-head self-attention, while the texture path is built on the stacked convolution operation.

Autonomous Driving Decision Making +2

TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation

1 code implementation19 May 2021 Junxiao Chen, Jia Wei, Rui Li

In this paper, we propose a novel target-aware generative adversarial network called TarGAN, which is a generic multi-modality medical image translation model capable of (1) learning multi-modality medical image translation without relying on paired data, (2) enhancing quality of target area generation with the help of target area labels.


A unified Neural Network Approach to E-CommerceRelevance Learning

no code implementations26 Apr 2021 Yunjiang Jiang, Yue Shang, Rui Li, Wen-Yun Yang, Guoyu Tang, Chaoyi Ma, Yun Xiao, Eric Zhao

We describe a highly-scalable feed-forward neural model to provide relevance score for (query, item) pairs, using only user query and item title as features, and both user click feedback as well as limited human ratings as labels.

Information Retrieval Retrieval

A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images

1 code implementation25 Apr 2021 Libo Wang, Rui Li, Chenxi Duan, Ce Zhang, Xiaoliang Meng, Shenghui Fang

The fully convolutional network (FCN) with an encoder-decoder architecture has been the standard paradigm for semantic segmentation.

Semantic Segmentation

From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search

no code implementations24 Mar 2021 Rui Li, Yunjiang Jiang, WenYun Yang, Guoyu Tang, Songlin Wang, Chaoyi Ma, wei he, Xi Xiong, Yun Xiao, Eric Yihong Zhao

We introduce deep learning models to the two most important stages in product search at JD. com, one of the largest e-commerce platforms in the world.

Re-Ranking Retrieval +1

Scale-aware Neural Network for Semantic Segmentation of Multi-resolution Remote Sensing Images

no code implementations14 Mar 2021 Libo Wang, Ce Zhang, Rui Li, Chenxi Duan, Xiaoliang Meng, Peter M. Atkinson

However, MSR images suffer from two critical issues: 1) increased scale variation of geo-objects and 2) loss of detailed information at coarse spatial resolutions.

Scene Understanding Semantic Segmentation

A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images

2 code implementations16 Feb 2021 Rui Li, Shunyi Zheng, Ce Zhang, Chenxi Duan, Libo Wang

Based on FPN and AAM, a novel framework named Attention Aggregation Feature Pyramid Network (A2-FPN) is developed for semantic segmentation of fine-resolution remotely sensed images.

Decision Making Scene Understanding +1

Learning Depth via Leveraging Semantics: Self-supervised Monocular Depth Estimation with Both Implicit and Explicit Semantic Guidance

no code implementations11 Feb 2021 Rui Li, Xiantuo He, Danna Xue, Shaolin Su, Qing Mao, Yu Zhu, Jinqiu Sun, Yanning Zhang

While the mappings between image and pixel-wise depth are well-studied in current methods, the correlation between image, depth and scene semantics, however, is less considered.

Monocular Depth Estimation

Adaptive Processor Frequency Adjustment for Mobile Edge Computing with Intermittent Energy Supply

no code implementations10 Feb 2021 Tiansheng Huang, Weiwei Lin, Xiaobin Hong, Xiumin Wang, Qingbo Wu, Rui Li, Ching-Hsien Hsu, Albert Y. Zomaya

With astonishing speed, bandwidth, and scale, Mobile Edge Computing (MEC) has played an increasingly important role in the next generation of connectivity and service delivery.


ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images

1 code implementation4 Feb 2021 Rui Li, Chenxi Duan

Specifically, the high-caliber performance of the convolutional neural network (CNN) heavily relies on fine-grained spatial details (fine resolution) and sufficient contextual information (large receptive fields), both of which trigger high computational costs.

Semantic Segmentation

Analytical Characterization and Design Space Exploration for Optimization of CNNs

1 code implementation24 Jan 2021 Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan

Moving data through the memory hierarchy is a fundamental bottleneck that can limit the performance of core algorithms of machine learning, such as convolutional neural networks (CNNs).

BIG-bench Machine Learning

Non-uniform Motion Deblurring with Blurry Component Divided Guidance

no code implementations15 Jan 2021 Pei Wang, Wei Sun, Qingsen Yan, Axi Niu, Rui Li, Yu Zhu, Jinqiu Sun, Yanning Zhang

To tackle the above problems, we present a deep two-branch network to deal with blurry images via a component divided module, which divides an image into two components based on the representation of blurry degree.

Blind Image Deblurring Image Deblurring +1

IntraTomo: Self-Supervised Learning-Based Tomography via Sinogram Synthesis and Prediction

1 code implementation ICCV 2021 Guangming Zang, Ramzi Idoughi, Rui Li, Peter Wonka, Wolfgang Heidrich

After getting estimated through the sinogram prediction module, the density field is consistently refined in the second module using local and non-local geometrical priors.

Computed Tomography (CT) Self-Supervised Learning +1

VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications

no code implementations22 Dec 2020 Jian Chen, Meng Ling, Rui Li, Petra Isenberg, Tobias Isenberg, Michael Sedlmair, Torsten Möller, Robert S. Laramee, Han-Wei Shen, Katharina Wünsche, Qiru Wang

We present the VIS30K dataset, a collection of 29, 689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST).

Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal

no code implementations20 Dec 2020 Chenxi Duan, Rui Li

In remote sensing images, the existence of the thin cloud is an inevitable and ubiquitous phenomenon that crucially reduces the quality of imageries and limits the scenarios of application.

Cloud Removal

Semantic-Guided Representation Enhancement for Self-supervised Monocular Trained Depth Estimation

no code implementations15 Dec 2020 Rui Li, Qing Mao, Pei Wang, Xiantuo He, Yu Zhu, Jinqiu Sun, Yanning Zhang

Based on this framework, we enhance the local feature representation by sampling and feeding the point-based features that locate on the semantic edges to an individual Semantic-guided Edge Enhancement module (SEEM), which is specifically designed for promoting depth estimation on the challenging semantic borders.

Depth Estimation Semantic Segmentation

Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich Domains

no code implementations NeurIPS 2020 Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne Haake

We propose to jointly analyze experts' eye movements and verbal narrations to discover important and interpretable knowledge patterns to better understand their decision-making processes.

Decision Making

Multi-stage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing Images

1 code implementation29 Nov 2020 Rui Li, Shunyi Zheng, Chenxi Duan, Jianlin Su, Ce Zhang

The attention mechanism can refine the extracted feature maps and boost the classification performance of the deep network, which has become an essential technique in computer vision and natural language processing.

Semantic Segmentation

Eliminating the Barriers: Demystifying Wi-Fi Baseband Design and Introducing the PicoScenes Wi-Fi Sensing Platform

2 code implementations20 Oct 2020 Zhiping Jiang, Tom H. Luan, Han Hao, Jing Wang, Xincheng Ren, Kun Zhao, Wei Xi, Yueshen Xu, Rui Li

Three barriers always hamper the research: unknown baseband design and its influence, inadequate hardware, and the lack of versatile and flexible measurement software.

Hardware Architecture

Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks

1 code implementation16 Oct 2020 Kishan Kc, Rui Li, Feng Cui, Anne Haake

Recently, graph neural networks have been proposed to effectively learn representations for biomedical entities and achieved state-of-the-art results in biomedical interaction prediction.

Link Prediction

Interpretable Structured Learning with Sparse Gated Sequence Encoder for Protein-Protein Interaction Prediction

1 code implementation16 Oct 2020 Kishan Kc, Feng Cui, Anne Haake, Rui Li

Although various deep learning models in Siamese architecture have been proposed to model PPIs from sequences, these methods are computationally expensive for a large number of PPIs due to the pairwise encoding process.

Multi-Attention-Network for Semantic Segmentation of Fine Resolution Remote Sensing Images

no code implementations3 Sep 2020 Rui Li, Shunyi Zheng, Chenxi Duan, Ce Zhang, Jianlin Su, P. M. Atkinson

A novel attention mechanism of kernel attention with linear complexity is proposed to alleviate the large computational demand in attention.

Management Semantic Segmentation

Thick Cloud Removal of Remote Sensing Images Using Temporal Smoothness and Sparsity-Regularized Tensor Optimization

no code implementations11 Aug 2020 Chenxi Duan, Jun Pan, Rui Li

In this paper, a novel thick cloud removal method for remote sensing images based on temporal smoothness and sparsity-regularized tensor optimization (TSSTO) is proposed.

Cloud Removal

Land Cover Classification from Remote Sensing Images Based on Multi-Scale Fully Convolutional Network

1 code implementation1 Aug 2020 Rui Li, Shunyi Zheng, Chenxi Duan, Ce Zhang

In this paper, a Multi-Scale Fully Convolutional Network (MSFCN) with multi-scale convolutional kernel is proposed to exploit discriminative representations from two-dimensional (2D) satellite images.

General Classification

Research on Fitness Function of Two Evolution Algorithms Used for Neutron Spectrum Unfolding

no code implementations30 Jul 2020 Rui Li, Jianbo Yang, Xianguo Tuo, Rui Shi

In this work, we investigated the performance of eight fitness functions attached to the genetic algorithm (GA) and the differential evolution algorithm (DEA) used for unfolding four neutron spectra selected from the IAEA 403 report.

Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation

2 code implementations29 Jul 2020 Rui Li, Jianlin Su, Chenxi Duan, Shunyi Zheng

In this paper, to remedy this deficiency, we propose a Linear Attention Mechanism which is approximate to dot-product attention with much less memory and computational costs.

Semantic Segmentation

MACU-Net for Semantic Segmentation of Fine-Resolution Remotely Sensed Images

2 code implementations26 Jul 2020 Rui Li, Chenxi Duan, Shunyi Zheng, Ce Zhang, Peter M. Atkinson

In this Letter, we incorporate multi-scale features generated by different layers of U-Net and design a multi-scale skip connected and asymmetric-convolution-based U-Net (MACU-Net), for segmentation using fine-resolution remotely sensed images.

Image Segmentation Management +2

Model Adaptation: Unsupervised Domain Adaptation Without Source Data

no code implementations CVPR 2020 Rui Li, Qianfen Jiao, Wenming Cao, Hau-San Wong, Si Wu

We aim to explore how to rely only on unlabeled target data to improve performance of an existing source prediction model on the target domain, since labeled source data may not be available in some real-world scenarios due to data privacy issues.

Unsupervised Domain Adaptation

LiteDenseNet: A Lightweight Network for Hyperspectral Image Classification

no code implementations17 Apr 2020 Rui Li, Chenxi Duan

Hyperspectral Image (HSI) classification based on deep learning has been an attractive area in recent years.

Classification General Classification +1

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

no code implementations20 Feb 2020 Hanshu Cai, Yiwen Gao, Shuting Sun, Na Li, Fuze Tian, Han Xiao, Jianxiu Li, Zhengwu Yang, Xiaowei Li, Qinglin Zhao, Zhenyu Liu, Zhijun Yao, Minqiang Yang, Hong Peng, Jing Zhu, Xiaowei Zhang, Guoping Gao, Fang Zheng, Rui Li, Zhihua Guo, Rong Ma, Jing Yang, Lan Zhang, Xiping Hu, Yumin Li, Bin Hu

The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications.


Robust Data Preprocessing for Machine-Learning-Based Disk Failure Prediction in Cloud Production Environments

no code implementations20 Dec 2019 Shujie Han, Jun Wu, Erci Xu, Cheng He, Patrick P. C. Lee, Yi Qiang, Qixing Zheng, Tao Huang, Zixi Huang, Rui Li

To provide proactive fault tolerance for modern cloud data centers, extensive studies have proposed machine learning (ML) approaches to predict imminent disk failures for early remedy and evaluated their approaches directly on public datasets (e. g., Backblaze SMART logs).

BIG-bench Machine Learning

Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes

no code implementations NeurIPS 2019 Rui Li

This paper studies statistical characteristics of multivariate observations with irregular changes in their covariance structures across input space.

Gaussian Processes

Validation of image-guided cochlear implant programming techniques

no code implementations23 Sep 2019 Yiyuan Zhao, Jianing Wang, Rui Li, Robert F. Labadie, Benoit M. Dawant, Jack H. Noble

In this article, we create a ground truth dataset with conventional CT and micro-CT images of 35 temporal bone specimens to both rigorously characterize the accuracy of these two steps and assess how inaccuracies in these steps affect the overall results.


A Convolutional Neural Network with Mapping Layers for Hyperspectral Image Classification

no code implementations26 Aug 2019 Rui Li, Zhibin Pan, Yang Wang, Ping Wang

In this paper, we propose a convolutional neural network with mapping layers (MCNN) for hyperspectral image (HSI) classification.

Classification General Classification +1

Adaptive Noise Injection: A Structure-Expanding Regularization for RNN

no code implementations25 Jul 2019 Rui Li, Kai Shuang, Mengyu Gu, Sen Su

Due to the adaptive noises can be improved as the training processes, its negative effects can be weakened and even transformed into a positive effect to further improve the expressiveness of the main-branch RNN.

Language Modelling

Neural Embedding for Physical Manipulations

no code implementations13 Jul 2019 Lingzhi Zhang, Andong Cao, Rui Li, Jianbo Shi

In common real-world robotic operations, action and state spaces can be vast and sometimes unknown, and observations are often relatively sparse.

Use of OWL and Semantic Web Technologies at Pinterest

no code implementations3 Jul 2019 Rafael S. Gonçalves, Matthew Horridge, Rui Li, Yu Liu, Mark A. Musen, Csongor I. Nyulas, Evelyn Obamos, Dhananjay Shrouty, David Temple

In this paper, we present the engineering of an OWL ontology---the Pinterest Taxonomy---that forms the core of Pinterest's knowledge graph, the Pinterest Taste Graph.

Imitating Targets from all sides: An Unsupervised Transfer Learning method for Person Re-identification

no code implementations10 Apr 2019 Jiajie Tian, Zhu Teng, Rui Li, Yan Li, Baopeng Zhang, Jianping Fan

Person re-identification (Re-ID) models usually show a limited performance when they are trained on one dataset and tested on another dataset due to the inter-dataset bias (e. g. completely different identities and backgrounds) and the intra-dataset difference (e. g. camera invariance).

Person Re-Identification Transfer Learning

GNE: a deep learning framework for gene network inference by aggregating biological information

1 code implementation BMC Systems Biology 2019 Kishan KC, Rui Li, Feng Cui, Qi Yu, Anne R. Haake

However, it is still a challenging task to aggregate heterogeneous biological information such as gene expression and gene interactions to achieve more accurate inference for prediction and discovery of new gene interactions.

 Ranked #1 on Gene Interaction Prediction on BioGRID(yeast) (using extra training data)

Gene Interaction Prediction Link Prediction

Deep Distribution Regression

1 code implementation14 Mar 2019 Rui Li, Howard D. Bondell, Brian J. Reich

Due to their flexibility and predictive performance, machine-learning based regression methods have become an important tool for predictive modeling and forecasting.

Decision Making General Classification +2

Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps

no code implementations26 Nov 2018 Camilo Bermudez, William Rodriguez, Yuankai Huo, Allison E. Hainline, Rui Li, Robert Shults, Pierre D. DHaese, Peter E. Konrad, Benoit M. Dawant, Bennett A. Landman

We show an improvement in the classification of intraoperative stimulation coordinates as a positive response in reduction of symptoms with AUC of 0. 670 compared to a baseline registration-based approach, which achieves an AUC of 0. 627 (p < 0. 01).

Anatomy BIG-bench Machine Learning +1

Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets with Multi-stream Inputs

no code implementations22 Nov 2018 Chaoyun Zhang, Rui Li, Woojin Kim, Daesub Yoon, Paul Patras

Experiments conducted with a dataset that we collect in a mock-up car environment demonstrate that the proposed InterCNN with MobileNet convolutional blocks can classify 9 different behaviors with 73. 97% accuracy, and 5 'aggregated' behaviors with 81. 66% accuracy.

Classification General Classification

Fast Symbolic 3D Registration Solution

4 code implementations12 May 2018 Jin Wu, Ming Liu, Zebo Zhou, Rui Li

3D registration has always been performed invoking singular value decomposition (SVD) or eigenvalue decomposition (EIG) in real engineering practices.

Participation of an energy hub in electricity and heat distribution markets: An mpec approach

1 code implementation IEEE Transactions on Smart Grid 2018 Rui Li, Wei Wei, Shengwei Mei, Qinran Hu, Qiuwei Wu

A mathematic program with equilibrium constraints (MPEC) model is proposed to study the strategic behaviors of a profit-driven energy hub in the electricity market and heating market under the background of energy system integration.

Patch-based Texture Synthesis for Image Inpainting

no code implementations5 May 2016 Tao Zhou, Brian Johnson, Rui Li

We form it as an optimization problem that identifies the potential patches for synthesis from an coarse-to-fine manner.

Image Inpainting Image Retrieval +2

Multiobjective Optimization of Classifiers by Means of 3-D Convex Hull Based Evolutionary Algorithm

no code implementations18 Dec 2014 Jiaqi Zhao, Vitor Basto Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Michael T. M. Emmerich

The design of the algorithm proposed in this paper is inspired by indicator-based evolutionary algorithms, where first a performance indicator for a solution set is established and then a selection operator is designed that complies with the performance indicator.

Classification General Classification +2

Image Understanding from Experts' Eyes by Modeling Perceptual Skill of Diagnostic Reasoning Processes

no code implementations CVPR 2013 Rui Li, Pengcheng Shi, Anne R. Haake

Eliciting and representing experts' remarkable perceptual capability of locating, identifying and categorizing objects in images specific to their domains of expertise will benefit image understanding in terms of transferring human domain knowledge and perceptual expertise into image-based computational procedures.

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