Search Results for author: Hu Wang

Found 32 papers, 9 papers with code

Multi-modal Learning with Missing Modality via Shared-Specific Feature Modelling

no code implementations CVPR 2023 Hu Wang, Yuanhong Chen, Congbo Ma, Jodie Avery, Louise Hull, Gustavo Carneiro

This is achieved from a strategy that relies on auxiliary tasks based on distribution alignment and domain classification, in addition to a residual feature fusion procedure.

Classification Image Segmentation +2

Distilling Missing Modality Knowledge from Ultrasound for Endometriosis Diagnosis with Magnetic Resonance Images

no code implementations5 Jul 2023 Yuan Zhang, Hu Wang, David Butler, Minh-Son To, Jodie Avery, M Louise Hull, Gustavo Carneiro

Next, we distill the knowledge from the teacher TVUS POD obliteration detector to train the student MRI model by minimizing a regression loss that approximates the output of the student to the teacher using unpaired TVUS and MRI data.

Knowledge Distillation

A Closer Look at Audio-Visual Semantic Segmentation

1 code implementation6 Apr 2023 Yuanhong Chen, Yuyuan Liu, Hu Wang, Fengbei Liu, Chong Wang, Gustavo Carneiro

In this work, we propose a new strategy to build cost-effective and relatively unbiased audio-visual semantic segmentation benchmarks.

audio-visual learning Contrastive Learning

Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation

1 code implementation21 Sep 2022 Yuanhong Chen, Hu Wang, Chong Wang, Yu Tian, Fengbei Liu, Michael Elliott, Davis J. McCarthy, Helen Frazer, Gustavo Carneiro

When analysing screening mammograms, radiologists can naturally process information across two ipsilateral views of each breast, namely the cranio-caudal (CC) and mediolateral-oblique (MLO) views.

M^4I: Multi-modal Models Membership Inference

1 code implementation15 Sep 2022 Pingyi Hu, Zihan Wang, Ruoxi Sun, Hu Wang, Minhui Xue

To achieve this, we propose Multi-modal Models Membership Inference (M^4I) with two attack methods to infer the membership status, named metric-based (MB) M^4I and feature-based (FB) M^4I, respectively.

Image Captioning Inference Attack +2

BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification

2 code implementations ICCV 2023 Yuanhong Chen, Fengbei Liu, Hu Wang, Chong Wang, Yu Tian, Yuyuan Liu, Gustavo Carneiro

Deep learning methods have shown outstanding classification accuracy in medical imaging problems, which is largely attributed to the availability of large-scale datasets manually annotated with clean labels.

Multi-Label Classification

Risk and return prediction for pricing portfolios of non-performing consumer credit

no code implementations28 Oct 2021 Siyi Wang, Xing Yan, Bangqi Zheng, Hu Wang, Wangli Xu, Nanbo Peng, Qi Wu

We design a system for risk-analyzing and pricing portfolios of non-performing consumer credit loans.

Dependency Structure for News Document Summarization

no code implementations23 Sep 2021 Congbo Ma, Wei Emma Zhang, Hu Wang, Shubham Gupta, Mingyu Guo

In this work, we develop a neural network based model which leverages dependency parsing to capture cross-positional dependencies and grammatical structures.

Dependency Parsing Document Summarization +1

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography

no code implementations20 Jul 2021 Zihan Wang, Olivia Byrnes, Hu Wang, Ruoxi Sun, Congbo Ma, Huaming Chen, Qi Wu, Minhui Xue

The advancement of secure communication and identity verification fields has significantly increased through the use of deep learning techniques for data hiding.

Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Federated Learning

no code implementations20 May 2021 Xiaolin Chen, Shuai Zhou, Bei guan, Kai Yang, Hao Fan, Hu Wang, Yongji Wang

With this key observation, we protect data privacy and allow the disclosure of feature meaning by concealing decision paths and adapt a communication-efficient secure computation method for inference outputs.

BIG-bench Machine Learning Federated Learning +1

Kernel Adversarial Learning for Real-world Image Super-resolution

no code implementations19 Apr 2021 Hu Wang, Congbo Ma, Jianpeng Zhang, Gustavo Carneiro

Current deep image super-resolution (SR) approaches attempt to restore high-resolution images from down-sampled images or by assuming degradation from simple Gaussian kernels and additive noises.

Image Super-Resolution

Oriole: Thwarting Privacy against Trustworthy Deep Learning Models

no code implementations23 Feb 2021 Liuqiao Chen, Hu Wang, Benjamin Zi Hao Zhao, Minhui Xue, Haifeng Qian

Deep Neural Networks have achieved unprecedented success in the field of face recognition such that any individual can crawl the data of others from the Internet without their explicit permission for the purpose of training high-precision face recognition models, creating a serious violation of privacy.

Data Poisoning Face Recognition +2

Delayed Rewards Calibration via Reward Empirical Sufficiency

no code implementations21 Feb 2021 Yixuan Liu, Hu Wang, Xiaowei Wang, Xiaoyue Sun, Liuyue Jiang, Minhui Xue

Therefore, a purify-trained classifier is designed to obtain the distribution and generate the calibrated rewards.

Multi-intersection Traffic Optimisation: A Benchmark Dataset and a Strong Baseline

no code implementations24 Jan 2021 Hu Wang, Hao Chen, Qi Wu, Congbo Ma, Yidong Li, Chunhua Shen

To address these issues, in this work we carefully design our settings and propose a new dataset including both synthetic and real traffic data in more complex scenarios.

Memory-Gated Recurrent Networks

1 code implementation24 Dec 2020 Yaquan Zhang, Qi Wu, Nanbo Peng, Min Dai, Jing Zhang, Hu Wang

The essence of multivariate sequential learning is all about how to extract dependencies in data.

Time Series Time Series Analysis

Fully Quantized Image Super-Resolution Networks

1 code implementation29 Nov 2020 Hu Wang, Peng Chen, Bohan Zhuang, Chunhua Shen

With the rising popularity of intelligent mobile devices, it is of great practical significance to develop accurate, realtime and energy-efficient image Super-Resolution (SR) inference methods.

Image Super-Resolution Quantization

Robust Data Hiding Using Inverse Gradient Attention

1 code implementation21 Nov 2020 Honglei Zhang, Hu Wang, Yuanzhouhan Cao, Chunhua Shen, Yidong Li

In deep data hiding models, to maximize the encoding capacity, each pixel of the cover image ought to be treated differently since they have different sensitivities w. r. t.

Multi-document Summarization via Deep Learning Techniques: A Survey

no code implementations10 Nov 2020 Congbo Ma, Wei Emma Zhang, Mingyu Guo, Hu Wang, Quan Z. Sheng

Multi-document summarization (MDS) is an effective tool for information aggregation that generates an informative and concise summary from a cluster of topic-related documents.

Document Summarization Multi-Document Summarization

Randomized Online CP Decomposition

no code implementations21 Jul 2020 Congbo Ma, Xiaowei Yang, Hu Wang

The experimental results on synthetic data and real-world data show the ROCP algorithm is able to cope with CP decomposition for large-scale tensors with arbitrary number of dimensions.

Multi-label Thoracic Disease Image Classification with Cross-Attention Networks

no code implementations21 Jul 2020 Congbo Ma, Hu Wang, Steven C. H. Hoi

Automated disease classification of radiology images has been emerging as a promising technique to support clinical diagnosis and treatment planning.

Classification General Classification +2

Soft Expert Reward Learning for Vision-and-Language Navigation

no code implementations ECCV 2020 Hu Wang, Qi Wu, Chunhua Shen

In this paper, we introduce a Soft Expert Reward Learning (SERL) model to overcome the reward engineering designing and generalisation problems of the VLN task.

Reinforcement Learning (RL) Vision and Language Navigation

Unsupervised Representation Learning by Predicting Random Distances

2 code implementations22 Dec 2019 Hu Wang, Guansong Pang, Chunhua Shen, Congbo Ma

To enable unsupervised learning on those domains, in this work we propose to learn features without using any labelled data by training neural networks to predict data distances in a randomly projected space.

Anomaly Detection Clustering +1

Image-based reconstruction for the impact problems by using DPNNs

no code implementations8 Apr 2019 Yu Li, Hu Wang, Wenquan Shuai, Honghao Zhang, Yong Peng

Therefore, in this study, an improved ReConNN method is proposed to address the mentioned weaknesses.

Image-Based Reconstruction for a 3D-PFHS Heat Transfer Problem by ReConNN

no code implementations6 Nov 2018 Yu Li, Hu Wang, Xinjian Deng

Therefore, an image-based reconstruction model of a heat transfer process for a 3D-PFHS is established.

An Adaptive Population Size Differential Evolution with Novel Mutation Strategy for Constrained Optimization

no code implementations11 May 2018 Yuan Fu, Hu Wang, Meng-Zhu Yang

To achieve the aim of searching the feasible solutions accurately, an adaptive population size method and an adaptive mutation strategy are proposed in the paper.

Reconstruction of Simulation-Based Physical Field by Reconstruction Neural Network Method

no code implementations19 Apr 2018 Yu Li, Hu Wang, Kangjia Mo, Tao Zeng

In such a framework, a reconstruction neural network (ReConNN) model designed for simulation-based physical field's reconstruction is proposed.

ReNN: Rule-embedded Neural Networks

no code implementations30 Jan 2018 Hu Wang

The complexity of neural networks can be reduced since long-term dependencies are not modeled with neural connections, and thus the amount of data needed to optimize the neural networks can be reduced.

Time Series Time Series Analysis

Can CNN Construct Highly Accurate Models Efficiently for High-Dimensional Problems in Complex Product Designs?

no code implementations15 Nov 2017 Yu Li, Hu Wang, Juanjuan Liu

In order to evaluate the proposed CNN metamodel for hundreds-dimensional and strong nonlinear problems, CNN is compared with other metamodeling techniques.

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