Search Results for author: Wen Jiang

Found 22 papers, 4 papers with code

Analysing Wideband Absorbance Immittance in Normal and Ears with Otitis Media with Effusion Using Machine Learning

no code implementations4 Mar 2021 Emad M. Grais, Xiaoya Wang, Jie Wang, Fei Zhao, Wen Jiang, Yuexin Cai, Lifang Zhang, Qingwen Lin, Haidi Yang

Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation of WAI results.

Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks

no code implementations12 Feb 2021 Hansheng Xue, Luwei Yang, Vaibhav Rajan, Wen Jiang, Yi Wei, Yu Lin

A large number of network embedding methods exist to learn vectorial node representations from general graphs with both homogeneous and heterogeneous node and edge types, including some that can specifically model the distinct properties of bipartite networks.

Link Prediction Network Embedding +1

Pseudo-Loss Confidence Metric for Semi-Supervised Few-Shot Learning

no code implementations ICCV 2021 Kai Huang, Jie Geng, Wen Jiang, Xinyang Deng, Zhe Xu

Most semi-supervised few-shot learning methods select pseudo-labeled data of unlabeled set by task-specific confidence estimation.

Few-Shot Learning

Coherent Reconstruction of Multiple Humans from a Single Image

1 code implementation CVPR 2020 Wen Jiang, Nikos Kolotouros, Georgios Pavlakos, Xiaowei Zhou, Kostas Daniilidis

Our goal is to train a single network that learns to avoid these problems and generate a coherent 3D reconstruction of all the humans in the scene.

3D Depth Estimation 3D Human Reconstruction +4

Deep Snake for Real-Time Instance Segmentation

1 code implementation CVPR 2020 Sida Peng, Wen Jiang, Huaijin Pi, Xiuli Li, Hujun Bao, Xiaowei Zhou

Based on deep snake, we develop a two-stage pipeline for instance segmentation: initial contour proposal and contour deformation, which can handle errors in object localization.

Object Localization Real-time Instance Segmentation +2

On the negation of a Dempster-Shafer belief structure based on maximum uncertainty allocation

no code implementations29 Jan 2019 Xinyang Deng, Wen Jiang

Probability theory and Dempster-Shafer theory are two germane theories to represent and handle uncertain information.

A total uncertainty measure for D numbers based on belief intervals

no code implementations25 Dec 2017 Xinyang Deng, Wen Jiang

As a generalization of Dempster-Shafer theory, the theory of D numbers is a new theoretical framework for uncertainty reasoning.

D numbers theory based game-theoretic framework in adversarial decision making under fuzzy environment

no code implementations25 Nov 2017 Xinyang Deng, Wen Jiang

Within the proposed framework or model, fuzzy set theory is used to model the uncertain evaluations of decision makers to alternatives, the non-exclusiveness among fuzzy evaluations are taken into consideration by using DNT, and the conflict of interests among decision makers is considered in a two-person non-constant sum game theory perspective.

Decision Making Skeleton Based Action Recognition

Uncertainty measurement with belief entropy on interference effect in Quantum-Like Bayesian Networks

no code implementations8 Sep 2017 Zhiming Huang, Lin Yang, Wen Jiang

Social dilemmas have been regarded as the essence of evolution game theory, in which the prisoner's dilemma game is the most famous metaphor for the problem of cooperation.

An evidential Markov decision making model

no code implementations10 May 2017 Zichang He, Wen Jiang

However, the state is allowed to be uncertain in the EM model before the final decision is made.

Decision Making

Quantum Mechanical Approach to Modelling Reliability of Sensor Reports

no code implementations17 Apr 2017 Zichang He, Wen Jiang

Dempster-Shafer evidence theory is wildly applied in multi-sensor data fusion.

Exploring the Combination Rules of D Numbers From a Perspective of Conflict Redistribution

no code implementations15 Mar 2017 Xinyang Deng, Wen Jiang

Dempster-Shafer theory of evidence is widely applied to uncertainty modelling and knowledge reasoning because of its advantages in dealing with uncertain information.

Evidential supplier selection based on interval data fusion

no code implementations6 Mar 2017 Zichang He, Wen Jiang

However, the weights of criteria are kept as interval numbers to generate interval BPAs and do the fusion of interval BPAs.

Decision Making

A quantum dynamic belief model to explain the interference effects of categorization on decision making

no code implementations6 Mar 2017 Zichang He, Wen Jiang

However, the categorization process may interfere the decision making result and the law of total probability can be violated in some situations.

Decision Making

A new belief Markov chain model and its application in inventory prediction

no code implementations6 Mar 2017 Zichang He, Wen Jiang

The new belief Markov chain model overcomes the shortcomings of classical Markov chain and has an efficient ability in dealing with uncertain information.

A quantum dynamic belief decision making model

no code implementations6 Mar 2017 Zichang He, Wen Jiang

The uncertainty in actions is represented as an extra uncertainty state.

Decision Making

A modified Physarum-inspired model for the user equilibrium traffic assignment problem

no code implementations19 Dec 2016 Shuai Xu, Wen Jiang, Yehang Shou

The user equilibrium traffic assignment principle is very important in the traffic assignment problem.

A correlation coefficient of belief functions

no code implementations16 Dec 2016 Wen Jiang

The correlation coefficient can be used to measure the similarity of evidence in Dempster-Shafer evidence theory.

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