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05/08/2022
Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks
The Graph Convolutional Networks (GCNs) have achieved excellent results ...
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09/29/2021
Adaptive Multi-layer Contrastive Graph Neural Networks
We present Adaptive Multi-layer Contrastive Graph Neural Networks (AMC-G...
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06/26/2021
ShapeEditer: a StyleGAN Encoder for Face Swapping
In this paper, we propose a novel encoder, called ShapeEditor, for high-...
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06/03/2021
Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout
Deep neural networks(DNNs) is vulnerable to be attacked by adversarial e...
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05/25/2021
AdaGCN:Adaptive Boosting Algorithm for Graph Convolutional Networks on Imbalanced Node Classification
The Graph Neural Network (GNN) has achieved remarkable success in graph ...
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10/22/2020
Defense-guided Transferable Adversarial Attacks
Though deep neural networks perform challenging tasks excellently, they ...
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03/26/2020
Neural encoding and interpretation for high-level visual cortices based on fMRI using image caption features
On basis of functional magnetic resonance imaging (fMRI), researchers ar...
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03/13/2020
BigGAN-based Bayesian reconstruction of natural images from human brain activity
In the visual decoding domain, visually reconstructing presented images ...
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02/01/2020
AdvJND: Generating Adversarial Examples with Just Noticeable Difference
Compared with traditional machine learning models, deep neural networks ...
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09/17/2019
HAD-GAN: A Human-perception Auxiliary Defense GAN model to Defend Adversarial Examples
Adversarial examples reveal the vulnerability and unexplained nature of ...
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07/27/2019
Effective and efficient ROI-wise visual encoding using an end-to-end CNN regression model and selective optimization
Recently, visual encoding based on functional magnetic resonance imaging...
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04/12/2019
Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense
In image classification of deep learning, adversarial examples where inp...
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02/23/2019
A visual encoding model based on deep neural networks and transfer learning
Background: Building visual encoding models to accurately predict visual...
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01/16/2018
Constraint-free Natural Image Reconstruction from fMRI Signals Based on Convolutional Neural Network
In recent years, research on decoding brain activity based on functional...
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01/02/2018
Accurate reconstruction of image stimuli from human fMRI based on the decoding model with capsule network architecture
In neuroscience, all kinds of computation models were designed to answer...
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07/29/2016