Search Results for author: Bin Liu

Found 84 papers, 16 papers with code

Detecting and Identifying Optical Signal Attacks on Autonomous Driving Systems

no code implementations20 Oct 2021 Jindi Zhang, Yifan Zhang, Kejie Lu, JianPing Wang, Kui Wu, Xiaohua Jia, Bin Liu

In our study, we use real data sets and the state-of-the-art machine learning model to evaluate our attack detection scheme and the results confirm the effectiveness of our detection method.

Autonomous Driving Object Detection

Unsupervised Finetuning

no code implementations18 Oct 2021 Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Bin Liu, Nenghai Yu

This problem is more challenging than the supervised counterpart, as the low data density in the small-scale target data is not friendly for unsupervised learning, leading to the damage of the pretrained representation and poor representation in the target domain.

Asymmetric Graph Representation Learning

no code implementations14 Oct 2021 Zhuo Tan, Bin Liu, Guosheng Yin

We define an incoming embedding and an outgoing embedding for each node to model its sending and receiving features respectively.

Graph Representation Learning

ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation

1 code implementation ICCV 2021 Zhenchao Jin, Bin Liu, Qi Chu, Nenghai Yu

Third, we compute the similarities between each pixel representation and the image-level contextual information, the semantic-level contextual information, respectively.

Semantic Segmentation

Consistent Relative Confidence and Label-Free Model Selection for Convolutional Neural Networks

no code implementations26 Aug 2021 Bin Liu

Present model selection methods require access to a batch of labeled data for defining a performance metric, such as the cross-entropy loss, the classification error rate, the negative log-likelihood, and so on.

Image Classification Model Selection

Detection of Illicit Drug Trafficking Events on Instagram: A Deep Multimodal Multilabel Learning Approach

no code implementations19 Aug 2021 Chuanbo Hu, Minglei Yin, Bin Liu, Xin Li, Yanfang Ye

Accordingly, accurate detection of illicit drug trafficking events (IDTEs) from social media has become even more challenging.


Identifying Illicit Drug Dealers on Instagram with Large-scale Multimodal Data Fusion

no code implementations18 Aug 2021 Chuanbo Hu, Minglei Yin, Bin Liu, Xin Li, Yanfang Ye

Unlike existing methods that focus on posting-based detection, we propose to tackle the problem of illicit drug dealer identification by constructing a large-scale multimodal dataset named Identifying Drug Dealers on Instagram (IDDIG).

Community Detection

Escaping the Gradient Vanishing: Periodic Alternatives of Softmax in Attention Mechanism

1 code implementation16 Aug 2021 Shulun Wang, Bin Liu, Feng Liu

Softmax is widely used in neural networks for multiclass classification, gate structure and attention mechanisms.

Abnormal Behavior Detection Based on Target Analysis

no code implementations29 Jul 2021 Luchuan Song, Bin Liu, Huihui Zhu, Qi Chu, Nenghai Yu

To this end, we propose a multivariate fusion method that analyzes each target through three branches: object, action and motion.

Cascaded Residual Density Network for Crowd Counting

no code implementations29 Jul 2021 Kun Zhao, Luchuan Song, Bin Liu, Qi Chu, Nenghai Yu

Crowd counting is a challenging task due to the issues such as scale variation and perspective variation in real crowd scenes.

Crowd Counting

Improve Unsupervised Pretraining for Few-label Transfer

no code implementations ICCV 2021 Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Bin Liu, Nenghai Yu

Unsupervised pretraining has achieved great success and many recent works have shown unsupervised pretraining can achieve comparable or even slightly better transfer performance than supervised pretraining on downstream target datasets.

Contrastive Learning

Robust Dynamic Multi-Modal Data Fusion: A Model Uncertainty Perspective

1 code implementation13 May 2021 Bin Liu

Then the problem of concern is formalized as a task of nonlinear non-Gaussian state filtering under model uncertainty, which is addressed by a dynamic model averaging (DMA) based particle filter (PF) algorithm.

Optimizing Area Under the Curve Measures via Matrix Factorization for Drug-Target Interaction Prediction

no code implementations1 May 2021 Bin Liu, Grigorios Tsoumakas

Area under the precision-recall curve (AUPR) that emphasizes the accuracy of top-ranked pairs and area under the receiver operating characteristic curve (AUC) that heavily punishes the existence of low ranked interacting pairs are two widely used evaluation metrics in the DTI prediction task.

Drug Discovery

Intelligent Decision Method for Main Control Parameters of Tunnel Boring Machine based on Multi-Objective Optimization of Excavation Efficiency and Cost

no code implementations29 Apr 2021 Bin Liu, Yaxu Wang, Guangzu Zhao, Bin Yang, Ruirui Wang, Dexiang Huang, Bin Xiang

Therefore, this paper proposes an intelligent decision method for the main control parameters of the TBM based on the multi-objective optimization of excavation efficiency and cost.

"Weak AI" is Likely to Never Become "Strong AI", So What is its Greatest Value for us?

no code implementations29 Mar 2021 Bin Liu

AI has surpassed humans across a variety of tasks such as image classification, playing games (e. g., go, "Starcraft" and poker), and protein structure prediction.

Image Classification Protein Structure Prediction +1

Diverse Semantic Image Synthesis via Probability Distribution Modeling

1 code implementation CVPR 2021 Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu, Bin Liu, Gang Hua, Nenghai Yu

In this paper, we propose a novel diverse semantic image synthesis framework from the perspective of semantic class distributions, which naturally supports diverse generation at semantic or even instance level.

Image Generation

Bayesian adversarial multi-node bandit for optimal smart grid protection against cyber attacks

no code implementations20 Feb 2021 Jianyu Xu, Bin Liu, Huadong Mo, Daoyi Dong

The cybersecurity of smart grids has become one of key problems in developing reliable modern power and energy systems.

A Random Algorithm for Profit Maximization with Multiple Adoptions in Online Social Networks

no code implementations15 Jan 2021 Tiantian Chen, Bin Liu, Wenjing Liu, Qizhi Fang, Jing Yuan, Weili Wu

Through "word of mouth" effects, information or product adoption could spread from some influential individuals to millions of users in social networks.

Social and Information Networks

Data Poisoning Attacks to Deep Learning Based Recommender Systems

no code implementations7 Jan 2021 Hai Huang, Jiaming Mu, Neil Zhenqiang Gong, Qi Li, Bin Liu, Mingwei Xu

Specifically, we formulate our attack as an optimization problem, such that the injected ratings would maximize the number of normal users to whom the target items are recommended.

Data Poisoning Recommendation Systems

Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery

1 code implementation22 Dec 2020 Bin Liu, Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas

In addition, WkNNIR exploits local imbalance to promote the influence of more reliable similarities on the interaction recovery and prediction processes.

Drug Discovery

Learning distributed sentence vectors with bi-directional 3D convolutions

no code implementations COLING 2020 Bin Liu, Liang Wang, Guosheng Yin

Similar to the Bi-LSTM, these n-gram detectors learn both forward and backward distributional semantic knowledge from the sentence tensor.

Sentence Embedding

Deep Time Delay Neural Network for Speech Enhancement with Full Data Learning

no code implementations11 Nov 2020 Cunhang Fan, Bin Liu, JianHua Tao, Jiangyan Yi, Zhengqi Wen, Leichao Song

This paper proposes a deep time delay neural network (TDNN) for speech enhancement with full data learning.

Speech Enhancement

Gated Recurrent Fusion with Joint Training Framework for Robust End-to-End Speech Recognition

no code implementations9 Nov 2020 Cunhang Fan, Jiangyan Yi, JianHua Tao, Zhengkun Tian, Bin Liu, Zhengqi Wen

The joint training framework for speech enhancement and recognition methods have obtained quite good performances for robust end-to-end automatic speech recognition (ASR).

automatic-speech-recognition End-To-End Speech Recognition +2

Enhanced Lidov-Kozai migration and the formation of the transiting giant planet WD1856+534b

no code implementations8 Oct 2020 Christopher E. O'Connor, Bin Liu, Dong Lai

By requiring that perturbations from the companion stars be able to overcome short-range forces and excite the planet's eccentricity to $e \simeq 1$, we obtain an absolute limit of $a_{1} \gtrsim 8 \, {\rm AU} \, (a_{3} / 1500 \, {\rm AU})^{6/7}$ for the planet's semi-major axis just before migration (where $a_{3}$ is the semi-major axis of the 'outer' orbit).

Earth and Planetary Astrophysics Solar and Stellar Astrophysics

Quantum droplets in two-dimensional optical lattices

no code implementations15 Sep 2020 Yiyin Zheng, Shantong Chen, Zhipeng Huang, Shixuan Dai, Bin Liu, Yongyao Li, Shurong Wang

We study the stability of zero-vorticity and vortex lattice quantum droplets (LQDs), which are described by a two-dimensional (2D) Gross-Pitaevskii (GP) equation with a periodic potential and Lee-Huang-Yang (LHY) term.

Pattern Formation and Solitons Quantum Physics

A Deep Learning Approach to Quasar Continuum Prediction

1 code implementation8 Jun 2020 Bin Liu, Rongmon Bordoloi

We apply iQNet and predict the continua of $\sim$3200 SDSS-DR16 quasar spectra at higher redshift ($2< z \leq 5$) and measure the redshift evolution of mean transmitted flux ($< F >$) in the Ly-$\alpha$ forest region.

Astrophysics of Galaxies

Multi-Label Sampling based on Local Label Imbalance

1 code implementation7 May 2020 Bin Liu, Konstantinos Blekas, Grigorios Tsoumakas

Experimental results on 13 multi-label datasets demonstrate the effectiveness of the proposed measure and sampling approaches for a variety of evaluation metrics, particularly in the case of an ensemble of classifiers trained on repeated samples of the original data.

Multi-Label Learning

Simultaneous Denoising and Dereverberation Using Deep Embedding Features

no code implementations6 Apr 2020 Cunhang Fan, Jian-Hua Tao, Bin Liu, Jiangyan Yi, Zhengqi Wen

In this paper, we propose a joint training method for simultaneous speech denoising and dereverberation using deep embedding features, which is based on the deep clustering (DC).

Deep Clustering Denoising +3

Density-Aware Graph for Deep Semi-Supervised Visual Recognition

no code implementations CVPR 2020 Suichan Li, Bin Liu, Dong-Dong Chen, Qi Chu, Lu Yuan, Nenghai Yu

Motivated by these limitations, this paper proposes to solve the SSL problem by building a novel density-aware graph, based on which the neighborhood information can be easily leveraged and the feature learning and label propagation can also be trained in an end-to-end way.

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

2 code implementations25 Mar 2020 Bin Liu, Chenxu Zhu, Guilin Li, Wei-Nan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu

By implementing a regularized optimizer over the architecture parameters, the model can automatically identify and remove the redundant feature interactions during the training process of the model.

Click-Through Rate Prediction Recommendation Systems

Deep Attention Fusion Feature for Speech Separation with End-to-End Post-filter Method

no code implementations17 Mar 2020 Cunhang Fan, Jian-Hua Tao, Bin Liu, Jiangyan Yi, Zhengqi Wen, Xuefei Liu

Secondly, to pay more attention to the outputs of the pre-separation stage, an attention module is applied to acquire deep attention fusion features, which are extracted by computing the similarity between the mixture and the pre-separated speech.

Deep Attention Speech Quality +1

Cross-modality Person re-identification with Shared-Specific Feature Transfer

no code implementations CVPR 2020 Yan Lu, Yue Wu, Bin Liu, Tianzhu Zhang, Baopu Li, Qi Chu, Nenghai Yu

In this paper, we tackle the above limitation by proposing a novel cross-modality shared-specific feature transfer algorithm (termed cm-SSFT) to explore the potential of both the modality-shared information and the modality-specific characteristics to boost the re-identification performance.

Cross-Modality Person Re-identification Person Re-Identification

Uncovering Insurance Fraud Conspiracy with Network Learning

no code implementations27 Feb 2020 Chen Liang, Ziqi Liu, Bin Liu, Jun Zhou, Xiaolong Li, Shuang Yang, Yuan Qi

In order to detect and prevent fraudulent insurance claims, we developed a novel data-driven procedure to identify groups of organized fraudsters, one of the major contributions to financial losses, by learning network information.

Fraud Detection Graph Learning

Concise and Effective Network for 3D Human Modeling from Orthogonal Silhouettes

1 code implementation25 Dec 2019 Bin Liu, Xiuping Liu, Zhi-Xin Yang, Charlie C. L. Wang

In this paper, we revisit the problem of 3D human modeling from two orthogonal silhouettes of individuals (i. e., front and side views).

GPRInvNet: Deep Learning-Based Ground Penetrating Radar Data Inversion for Tunnel Lining

no code implementations12 Dec 2019 Bin Liu, Yuxiao Ren, Hanchi Liu, Hui Xu, Zhengfang Wang, Anthony G. Cohn, Peng Jiang

The results have demonstrated that the GPRInvNet is capable of effectively reconstructing complex tunnel lining defects with clear boundaries.

GPR Time Series

Text classification with pixel embedding

no code implementations11 Nov 2019 Bin Liu, Guosheng Yin, Wenbin Du

The first two dimensions of the convolutional kernel size equal the size of the word image and the last dimension of the kernel size is $n$.

Classification General Classification +1

Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces

1 code implementation NeurIPS 2019 Yu Qi, Bin Liu, Yueming Wang, Gang Pan

Brain-computer interfaces (BCIs) have enabled prosthetic device control by decoding motor movements from neural activities.

Domain adversarial learning for emotion recognition

no code implementations24 Oct 2019 Zheng Lian, Jian-Hua Tao, Bin Liu, Jian Huang

The secondary task is to learn a common representation where speaker identities can not be distinguished.

Emotion Recognition

Conversational Emotion Analysis via Attention Mechanisms

no code implementations24 Oct 2019 Zheng Lian, Jian-Hua Tao, Bin Liu, Jian Huang

Different from the emotion recognition in individual utterances, we propose a multimodal learning framework using relation and dependencies among the utterances for conversational emotion analysis.

Emotion Recognition

Unsupervised Representation Learning with Future Observation Prediction for Speech Emotion Recognition

no code implementations24 Oct 2019 Zheng Lian, Jian-Hua Tao, Bin Liu, Jian Huang

Prior works on speech emotion recognition utilize various unsupervised learning approaches to deal with low-resource samples.

Fine-tuning Speech Emotion Recognition +2

Normal Estimation for 3D Point Clouds via Local Plane Constraint and Multi-scale Selection

no code implementations18 Oct 2019 Jun Zhou, Hua Huang, Bin Liu, Xiuping Liu

Then we use multi-task optimization to train the normal estimation and local plane classification tasks simultaneously. Also, to integrate the advantages of multi-scale results, a scale selection strategy is adopted, which is a data-driven approach for selecting the optimal scale around each point and encourages subnetwork specialization.

Sequential Learning for Dirichlet Process Mixtures

no code implementations pproximateinference AABI Symposium 2019 Chunlin Ji, Bin Liu, Yingkai Jiang, Ke Deng

We propose an evidence upper bound (EUBO) to act as the surrogate loss, and fit a DP mixture to the given data by minimizing the EUBO, which is equivalent to minimizing the KL-divergence between the target distribution and the DP mixture.

Variational Inference

Discriminative Learning for Monaural Speech Separation Using Deep Embedding Features

no code implementations23 Jul 2019 Cunhang Fan, Bin Liu, Jian-Hua Tao, Jiangyan Yi, Zhengqi Wen

Firstly, a DC network is trained to extract deep embedding features, which contain each source's information and have an advantage in discriminating each target speakers.

Deep Clustering Fine-tuning +1

Synthetic Oversampling of Multi-Label Data based on Local Label Distribution

2 code implementations2 May 2019 Bin Liu, Grigorios Tsoumakas

Class-imbalance is an inherent characteristic of multi-label data which affects the prediction accuracy of most multi-label learning methods.

Multi-Label Learning

A Large Scale Urban Surveillance Video Dataset for Multiple-Object Tracking and Behavior Analysis

no code implementations26 Apr 2019 Guojun Yin, Bin Liu, Huihui Zhu, Tao Gong, Nenghai Yu

Multiple-object tracking and behavior analysis have been the essential parts of surveillance video analysis for public security and urban management.

Multiple Object Tracking

Deep Learning Inversion of Electrical Resistivity Data

no code implementations10 Apr 2019 Bin Liu, Qian Guo, Shucai Li, Benchao Liu, Yuxiao Ren, Yonghao Pang, Xu Guo, Lanbo Liu, Peng Jiang

According to the comprehensive qualitative analysis and quantitative comparison, ERSInvNet with tier feature map, smooth constraints, and depth weighting function together achieve the best performance.

Model Selection

Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction

3 code implementations9 Apr 2019 Bin Liu, Ruiming Tang, Yingzhi Chen, Jinkai Yu, Huifeng Guo, Yuzhou Zhang

Easy-to-use, Modular and Extendible package of deep-learning based CTR models. DeepFM, DeepInterestNetwork(DIN), DeepInterestEvolutionNetwork(DIEN), DeepCrossNetwork(DCN), AttentionalFactorizationMachine(AFM), Neural Factorization Machine(NFM), AutoInt, Deep Session Interest Network(DSIN)

Click-Through Rate Prediction Recommendation Systems

Context and Attribute Grounded Dense Captioning

no code implementations CVPR 2019 Guojun Yin, Lu Sheng, Bin Liu, Nenghai Yu, Xiaogang Wang, Jing Shao

Dense captioning aims at simultaneously localizing semantic regions and describing these regions-of-interest (ROIs) with short phrases or sentences in natural language.

Harnessing Low-Fidelity Data to Accelerate Bayesian Optimization via Posterior Regularization

no code implementations11 Feb 2019 Bin Liu

Bayesian optimization (BO) is a powerful paradigm for derivative-free global optimization of a black-box objective function (BOF) that is expensive to evaluate.

Global Optimization

Deep Triplet Quantization

1 code implementation1 Feb 2019 Bin Liu, Yue Cao, Mingsheng Long, Jian-Min Wang, Jingdong Wang

We propose Deep Triplet Quantization (DTQ), a novel approach to learning deep quantization models from the similarity triplets.

Image Retrieval Quantization

Deep-Learning Inversion of Seismic Data

no code implementations23 Jan 2019 Shucai Li, Bin Liu, Yuxiao Ren, Yangkang Chen, Senlin Yang, Yunhai Wang, Peng Jiang

We propose a new method to tackle the mapping challenge from time-series data to spatial image in the field of seismic exploration, i. e., reconstructing the velocity model directly from seismic data by deep neural networks (DNNs).

Time Series

Deep Metric Transfer for Label Propagation with Limited Annotated Data

1 code implementation20 Dec 2018 Bin Liu, Zhirong Wu, Han Hu, Stephen Lin

In this paper, we propose a generic framework that utilizes unlabeled data to aid generalization for all three tasks.

Metric Learning Object Recognition +1

Real-Time Anomaly Detection With HMOF Feature

no code implementations12 Dec 2018 Huihui Zhu, Bin Liu, Guojun Yin, Yan Lu, Weihai Li, Nenghai Yu

Most existing methods are computation consuming, which cannot satisfy the real-time requirement.

Anomaly Detection Optical Flow Estimation

What and Where: A Context-based Recommendation System for Object Insertion

no code implementations24 Nov 2018 Song-Hai Zhang, Zhengping Zhou, Bin Liu, Xin Dong, Dun Liang, Peter Hall, Shi-Min Hu

In this work, we propose a novel topic consisting of two dual tasks: 1) given a scene, recommend objects to insert, 2) given an object category, retrieve suitable background scenes.

A Very Brief and Critical Discussion on AutoML

no code implementations9 Nov 2018 Bin Liu

This contribution presents a very brief and critical discussion on automated machine learning (AutoML), which is categorized here into two classes, referred to as narrow AutoML and generalized AutoML, respectively.


Cross-Modal Hamming Hashing

no code implementations ECCV 2018 Yue Cao , Bin Liu, Mingsheng Long, Jian-Min Wang

Extensive experiments demonstrate that CMHH can generate highly concentrated hash codes and achieve state-of-the-art cross-modal retrieval performance for both hash lookups and linear scan scenarios on three benchmark datasets, NUS-WIDE, MIRFlickr-25K, and IAPR TC-12.

Cross-Modal Retrieval

A Particle Filter based Multi-Objective Optimization Algorithm: PFOPS

no code implementations28 Aug 2018 Bin Liu, Yaochu Jin

To this end, we make an effort to extend the scope of application of the PFO paradigm to multi-objective optimization (MOO) cases.

Particle Filtering Methods for Stochastic Optimization with Application to Large-Scale Empirical Risk Minimization

no code implementations23 Jul 2018 Bin Liu

There is a recent interest in developing statistical filtering methods for stochastic optimization (FSO) by leveraging a probabilistic perspective of incremental proximity methods (IPMs).

Stochastic Optimization

Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition

no code implementations ECCV 2018 Guojun Yin, Lu Sheng, Bin Liu, Nenghai Yu, Xiaogang Wang, Jing Shao, Chen Change Loy

We show that by encouraging deep message propagation and interactions between local object features and global predicate features, one can achieve compelling performance in recognizing complex relationships without using any linguistic priors.

Deep Cauchy Hashing for Hamming Space Retrieval

no code implementations CVPR 2018 Yue Cao, Mingsheng Long, Bin Liu, Jian-Min Wang

Due to its computation efficiency and retrieval quality, hashing has been widely applied to approximate nearest neighbor search for large-scale image retrieval, while deep hashing further improves the retrieval quality by end-to-end representation learning and hash coding.

Image Retrieval Representation Learning

HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN

no code implementations CVPR 2018 Yue Cao, Bin Liu, Mingsheng Long, Jian-Min Wang

The main idea is to augment the training data with nearly real images synthesized from a new Pair Conditional Wasserstein GAN (PC-WGAN) conditioned on the pairwise similarity information.

Image Retrieval Representation Learning

Boosting Noise Robustness of Acoustic Model via Deep Adversarial Training

no code implementations2 May 2018 Bin Liu, Shuai Nie, Yaping Zhang, Dengfeng Ke, Shan Liang, Wenju Liu1

In realistic environments, speech is usually interfered by various noise and reverberation, which dramatically degrades the performance of automatic speech recognition (ASR) systems.

automatic-speech-recognition Speech Enhancement +1

Simultaneous Modeling of Multiple Complications for Risk Profiling in Diabetes Care

no code implementations19 Feb 2018 Bin Liu, Ying Li, Soumya Ghosh, Zhaonan Sun, Kenney Ng, Jianying Hu

The proposed method is favorable for healthcare applications because in additional to improved prediction performance, relationships among the different risks and risk factors are also identified.

Multi-Task Learning

Two Birds with One Stone: Transforming and Generating Facial Images with Iterative GAN

no code implementations16 Nov 2017 Dan Ma, Bin Liu, Zhao Kang, Jiayu Zhou, Jianke Zhu, Zenglin Xu

Generating high fidelity identity-preserving faces with different facial attributes has a wide range of applications.

Image Generation

Maximum Likelihood Estimation based on Random Subspace EDA: Application to Extrasolar Planet Detection

no code implementations18 Apr 2017 Bin Liu, Ke-Jia Chen

A population based searching method, called estimation of distribution algorithm (EDA), is adopted to explore the model parameter space starting from a batch of random locations.

Tensor Decomposition via Variational Auto-Encoder

no code implementations3 Nov 2016 Bin Liu, Zenglin Xu, Yingming Li

Another assumption of these methods is that a predefined rank should be known.

Tensor Decomposition

Student's t Distribution based Estimation of Distribution Algorithms for Derivative-free Global Optimization

no code implementations12 Aug 2016 Bin Liu, Shi Cheng, Yuhui Shi

Observing that the Student's t distribution has heavier and longer tails than the Gaussian, which may be beneficial for exploring the solution space, we propose a novel EDA algorithm termed ESTDA, in which the Student's t distribution, rather than Gaussian, is employed.

Global Optimization

Vision-based Traffic Flow Prediction using Dynamic Texture Model and Gaussian Process

no code implementations14 Jul 2016 Bin Liu, Hao Ji, Yi Dai

The proposed method consists of three elemental operators, that are dynamic texture model based motion segmentation, feature extraction and Gaussian process (GP) regression.

Motion Segmentation

Ternary Weight Networks

3 code implementations16 May 2016 Fengfu Li, Bo Zhang, Bin Liu

We introduce ternary weight networks (TWNs) - neural networks with weights constrained to +1, 0 and -1.

Model Compression

Robust video object tracking via Bayesian model averaging based feature fusion

no code implementations2 Apr 2016 Yi Dai, Bin Liu

In this article, we are concerned with tracking an object of interest in video stream.

Video Object Tracking

Robust video object tracking using particle filter with likelihood based feature fusion and adaptive template updating

no code implementations28 Sep 2015 Yi Dai, Bin Liu

In this solution, the bootstrap particle filter (PF) is initialized by an object detector, which models the time-evolving background of the video signal by an adaptive Gaussian mixture.

Video Object Tracking

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