728 citations · 1k across the 20 of their papers we have counts for
20 papers
SEVGGNet-LSTM: a fused deep learning model for ECG classification
Tongyue He, Yiming Chen, Junxin Chen +2
This paper presents a fused deep learning algorithm for ECG classification. It takes advantages of the combined convolutional and recurrent neural network for ECG classification, a…
GCT: Graph Co-Training for Semi-Supervised Few-Shot Learning
Rui Xu, Lei Xing, Shuai Shao +4
Few-shot learning (FSL), purposing to resolve the problem of data-scarce, has attracted considerable attention in recent years. A popular FSL framework contains two phases: (i) the…
CIM: Class-Irrelevant Mapping for Few-Shot Classification
Shuai Shao, Lei Xing, Yixin Chen +3
Few-shot classification (FSC) is one of the most concerned hot issues in recent years. The general setting consists of two phases: (1) Pre-train a feature extraction model (FEM) wi…
Secure Reversible Data Hiding in Encrypted Images Using Cipher-Feedback Secret Sharing
Zhongyun Hua, Yanxiang Wang, Shuang Yi +2
Reversible data hiding in encrypted images (RDH-EI) has attracted increasing attention, since it can protect the privacy of original images while the embedded data can be exactly e…
Detection of Deepfake Videos Using Long Distance Attention
Wei Lu, Lingyi Liu, Junwei Luo +3
With the rapid progress of deepfake techniques in recent years, facial video forgery can generate highly deceptive video contents and bring severe security threats. And detection o…
LineCounter: Learning Handwritten Text Line Segmentation by Counting
Deng Li, Yue Wu, Yicong Zhou
Handwritten Text Line Segmentation (HTLS) is a low-level but important task for many higher-level document processing tasks like handwritten text recognition. It is often formulate…
SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization
Deng Li, Yue Wu, Yicong Zhou
Inspired by the classic Sauvola local image thresholding approach, we systematically study it from the deep neural network (DNN) perspective and propose a new solution called Sauvo…
Bridging the Distribution Gap of Visible-Infrared Person Re-identification with Modality Batch Normalization
Wenkang Li, Qi Ke, Wenbin Chen +1
Visible-infrared cross-modality person re-identification (VI-ReID), whose aim is to match person images between visible and infrared modality, is a challenging cross-modality image…
Unified Batch All Triplet Loss for Visible-Infrared Person Re-identification
Wenkang Li, Ke Qi, Wenbin Chen +1
Visible-Infrared cross-modality person re-identification (VI-ReID), whose aim is to match person images between visible and infrared modality, is a challenging cross-modality image…
Learning Domain-invariant Graph for Adaptive Semi-supervised Domain Adaptation with Few Labeled Source Samples
Jinfeng Li, Weifeng Liu, Yicong Zhou +2
Domain adaptation aims to generalize a model from a source domain to tackle tasks in a related but different target domain. Traditional domain adaptation algorithms assume that eno…
Geometry Constrained Weakly Supervised Object Localization
Weizeng Lu, Xi Jia, Weicheng Xie +3
We propose a geometry constrained network, termed GC-Net, for weakly supervised object localization (WSOL). GC-Net consists of three modules: a detector, a generator and a classifi…
Universal chosen-ciphertext attack for a family of image encryption schemes
Junxin Chen, Lei Chen, Yicong Zhou
During the past decades, there is a great popularity employing nonlinear dynamics and permutation-substitution architecture for image encryption. There are three primary procedures…
Ensemble p-Laplacian Regularization for Remote Sensing Image Recognition
Xueqi Ma, Weifeng Liu, Dapeng Tao +1
Recently, manifold regularized semi-supervised learning (MRSSL) received considerable attention because it successfully exploits the geometry of the intrinsic data probability dist…
Hypergraph p-Laplacian Regularization for Remote Sensing Image Recognition
Xueqi Ma, Weifeng Liu, Shuying Li +1
It is of great importance to preserve locality and similarity information in semi-supervised learning (SSL) based applications. Graph based SSL and manifold regularization based SS…
Vision Recognition using Discriminant Sparse Optimization Learning
Qingxiang Feng, Yicong Zhou
To better select the correct training sample and obtain the robust representation of the query sample, this paper proposes a discriminant-based sparse optimization learning model.…
Discriminant Projection Representation-based Classification for Vision Recognition
Qingxiang Feng, Yicong Zhou
Representation-based classification methods such as sparse representation-based classification (SRC) and linear regression classification (LRC) have attracted a lot of attentions.…
Color Face Recognition using High-Dimension Quaternion-based Adaptive Representation
Qingxiang Feng, Yicong Zhou
Recently, quaternion collaborative representation-based classification (QCRC) and quaternion sparse representation-based classification (QSRC) have been proposed for color face rec…
Nonlinear Chaotic Processing Model
Zhongyun Hua, Yicong Zhou
Designing chaotic maps with complex dynamics is a challenging topic. This paper introduces the nonlinear chaotic processing (NCP) model, which contains six basic nonlinear operatio…
A Novel Latin Square Image Cipher
Yue Wu, Yicong Zhou, Joseph P. Noonan +2
In this paper, we introduce a symmetric-key Latin square image cipher (LSIC) for grayscale and color images. Our contributions to the image encryption community include 1) we devel…
Shannon Entropy based Randomness Measurement and Test for Image Encryption
Yue Wu, Joseph P. Noonan, Sos Agaian
The quality of image encryption is commonly measured by the Shannon entropy over the ciphertext image. However, this measurement does not consider to the randomness of local image…