Search Results for author: Linyuan Wang

Found 26 papers, 2 papers with code

Aligned with LLM: a new multi-modal training paradigm for encoding fMRI activity in visual cortex

no code implementations8 Jan 2024 Shuxiao Ma, Linyuan Wang, Senbao Hou, Bin Yan

Next, we use the contrast loss function to minimize the distance between the image embedding features and the text embedding features to complete the alignment operation of the stimulus image and text information.


A Multimodal Visual Encoding Model Aided by Introducing Verbal Semantic Information

no code implementations29 Aug 2023 Shuxiao Ma, Linyuan Wang, Bin Yan

A convolutional network then maps from this multimodal feature space to voxel space, constructing the multimodal visual information encoding network model.

Image Generation

MGTAB: A Multi-Relational Graph-Based Twitter Account Detection Benchmark

1 code implementation3 Jan 2023 Shuhao Shi, Kai Qiao, Jian Chen, Shuai Yang, Jie Yang, Baojie Song, Linyuan Wang, Bin Yan

However, in addition to low annotation quality, existing benchmarks generally have incomplete user relationships, suppressing graph-based account detection research.

Node Classification Stance Detection +1

LRIP-Net: Low-Resolution Image Prior based Network for Limited-Angle CT Reconstruction

no code implementations30 Jul 2022 Qifeng Gao, Rui Ding, Linyuan Wang, Bin Xue, Yuping Duan

The noisy incomplete projection data results in the ill-posedness of the inverse problems.

Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks

no code implementations8 May 2022 Shuhao Shi, Jian Chen, Kai Qiao, Shuai Yang, Linyuan Wang, Bin Yan

The Graph Convolutional Networks (GCNs) have achieved excellent results in node classification tasks, but the model's performance at low label rates is still unsatisfactory.

Node Classification

The Diversity Metrics of Sub-models based on SVD of Jacobians for Ensembles Adversarial Robustness

no code implementations AAAI Workshop AdvML 2022 Ruoxi Qin, Linyuan Wang, Xuehui Du, Bin Yan, Xingyuan Chen

A new constraints norm is proposed in model training based on these criteria to isolate adversarial transferability without any prior knowledge of adversarial samples.

Adversarial Robustness Attribute +2

RPT++: Customized Feature Representation for Siamese Visual Tracking

no code implementations23 Oct 2021 Ziang Ma, HaiTao Zhang, Linyuan Wang, Jun Yin

Polar pooling plays the role of enriching information collected from the semantic keypoints for stronger classification, while extreme pooling facilitates explicit visual patterns of the object boundary for accurate target state estimation.

Classification Visual Tracking

Adaptive Multi-layer Contrastive Graph Neural Networks

no code implementations29 Sep 2021 Shuhao Shi, Pengfei Xie, Xu Luo, Kai Qiao, Linyuan Wang, Jian Chen, Bin Yan

AMC-GNN generates two graph views by data augmentation and compares different layers' output embeddings of Graph Neural Network encoders to obtain feature representations, which could be used for downstream tasks.

Data Augmentation Self-Supervised Learning

Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout

no code implementations3 Jun 2021 Pengfei Xie, Linyuan Wang, Ruoxi Qin, Kai Qiao, Shuhao Shi, Guoen Hu, Bin Yan

In this paper, we propose a new gradient iteration framework, which redefines the relationship between the above three.

Dynamic Defense Approach for Adversarial Robustness in Deep Neural Networks via Stochastic Ensemble Smoothed Model

no code implementations6 May 2021 Ruoxi Qin, Linyuan Wang, Xingyuan Chen, Xuehui Du, Bin Yan

The defense strategies are particularly passive in these processes, and enhancing initiative of such strategies can be an effective way to get out of this arms race.

Adversarial Robustness Attribute

RPT: Learning Point Set Representation for Siamese Visual Tracking

no code implementations8 Aug 2020 Ziang Ma, Linyuan Wang, HaiTao Zhang, Wei Lu, Jun Yin

While remarkable progress has been made in robust visual tracking, accurate target state estimation still remains a highly challenging problem.

Semi-Supervised Video Object Segmentation Visual Tracking

Neural encoding and interpretation for high-level visual cortices based on fMRI using image caption features

no code implementations26 Mar 2020 Kai Qiao, Chi Zhang, Jian Chen, Linyuan Wang, Li Tong, Bin Yan

Except for deep network structure, the task or corresponding big dataset is also important for deep network models, but neglected by previous studies.

General Classification Image Classification

BigGAN-based Bayesian reconstruction of natural images from human brain activity

no code implementations13 Mar 2020 Kai Qiao, Jian Chen, Linyuan Wang, Chi Zhang, Li Tong, Bin Yan

In this study, we proposed a new GAN-based Bayesian visual reconstruction method (GAN-BVRM) that includes a classifier to decode categories from fMRI data, a pre-trained conditional generator to generate natural images of specified categories, and a set of encoding models and evaluator to evaluate generated images.

Conditional Image Generation Generative Adversarial Network

AdvJND: Generating Adversarial Examples with Just Noticeable Difference

no code implementations1 Feb 2020 Zifei Zhang, Kai Qiao, Lingyun Jiang, Linyuan Wang, Bin Yan

To alleviate the tradeoff between the attack success rate and image fidelity, we propose a method named AdvJND, adding visual model coefficients, just noticeable difference coefficients, in the constraint of a distortion function when generating adversarial examples.

Image Classification

Effective and efficient ROI-wise visual encoding using an end-to-end CNN regression model and selective optimization

1 code implementation27 Jul 2019 Kai Qiao, Chi Zhang, Jian Chen, Linyuan Wang, Li Tong, Bin Yan

Recently, visual encoding based on functional magnetic resonance imaging (fMRI) have realized many achievements with the rapid development of deep network computation.


Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense

no code implementations12 Apr 2019 Lingyun Jiang, Kai Qiao, Ruoxi Qin, Linyuan Wang, Jian Chen, Haibing Bu, Bin Yan

In image classification of deep learning, adversarial examples where inputs intended to add small magnitude perturbations may mislead deep neural networks (DNNs) to incorrect results, which means DNNs are vulnerable to them.

Adversarial Attack Image Classification

Category decoding of visual stimuli from human brain activity using a bidirectional recurrent neural network to simulate bidirectional information flows in human visual cortices

no code implementations19 Mar 2019 Kai Qiao, Jian Chen, Linyuan Wang, Chi Zhang, Lei Zeng, Li Tong, Bin Yan

Despite the hierarchically similar representations of deep network and human vision, visual information flows from primary visual cortices to high visual cortices and vice versa based on the bottom-up and top-down manners, respectively.

Neurons and Cognition

A Sinogram Inpainting Method based on Generative Adversarial Network for Limited-angle Computed Tomography

no code implementations10 Mar 2019 Ziheng Li, Wenkun Zhang, Linyuan Wang, Ailong Cai, Ningning Liang, Bin Yan, Lei LI

Limited-angle computed tomography (CT) image reconstruction is a challenging reconstruction problem in the fields of CT. With the development of deep learning, the generative adversarial network (GAN) perform well in image restoration by approximating the distribution of training sample data.

Medical Physics

A visual encoding model based on deep neural networks and transfer learning

no code implementations23 Feb 2019 Chi Zhang, Kai Qiao, Linyuan Wang, Li Tong, Guoen Hu, Ruyuan Zhang, Bin Yan

In this framework, we employ the transfer learning technique to incorporate a pre-trained DNN (i. e., AlexNet) and train a nonlinear mapping from visual features to brain activity.

Transfer Learning

Dissociable neural representations of adversarially perturbed images in convolutional neural networks and the human brain

no code implementations22 Dec 2018 Chi Zhang, Xiaohan Duan, Linyuan Wang, Yongli Li, Bin Yan, Guoen Hu, Ruyuan Zhang, Li Tong

Furthermore, we show that voxel-encoding models trained on regular images can successfully generalize to the neural responses to AI images but not AN images.

Constraint-free Natural Image Reconstruction from fMRI Signals Based on Convolutional Neural Network

no code implementations16 Jan 2018 Chi Zhang, Kai Qiao, Linyuan Wang, Li Tong, Ying Zeng, Bin Yan

Without semantic prior information, we present a novel method to reconstruct nature images from fMRI signals of human visual cortex based on the computation model of convolutional neural network (CNN).

Image Reconstruction

Accurate reconstruction of image stimuli from human fMRI based on the decoding model with capsule network architecture

no code implementations2 Jan 2018 Kai Qiao, Chi Zhang, Linyuan Wang, Bin Yan, Jian Chen, Lei Zeng, Li Tong

We firstly employed the CapsNet to train the nonlinear mapping from image stimuli to high-level capsule features, and from high-level capsule features to image stimuli again in an end-to-end manner.

Open-Ended Question Answering SSIM

Image Prediction for Limited-angle Tomography via Deep Learning with Convolutional Neural Network

no code implementations29 Jul 2016 Hanming Zhang, Liang Li, Kai Qiao, Linyuan Wang, Bin Yan, Lei LI, Guoen Hu

The qualitative and quantitative evaluations of experimental results indicate that the proposed method show a stable and prospective performance on artifacts reduction and detail recovery for limited angle tomography.

Computed Tomography (CT)

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