16 Result(s)
within
**zhan Gao
Machine Learning
-
Chapter and Conference Paper
VANet: A New Network for Multi-modal Self-supervised Learning from Video and Audio
A new Network for Multi-modal Self-Supervised Learning from Video and Audio (VANet) is proposed for video action recognition. To overcome the input issues of different modalities, we establish auxiliary tasks ...
-
Chapter and Conference Paper
MMT: Transformer for Multi-modal Multi-label Self-supervised Learning
We proposed a novel network, called Transformer, for Multi-modal Multi-label Self-Supervised Learning (MMT) in the context of video classification. Our approach tackles the input challenges arising from differ...
-
Chapter and Conference Paper
A Review of Visual Transformer Research
The development of Transformer in the field of computer vision has been very rapid in the past two years. Influenced by the development of Transformer in natural language processing and the research ideas of V...
-
Chapter and Conference Paper
New Predefined-Time Stability Theorem and Applications to the Fuzzy Stochastic Memristive Neural Networks with Impulsive Effects
The paper mainly investigates the issue of achieving predefined-time synchronization for fuzzy memristive neural networks with both impulsive effects and stochastic disturbances. Firstly, due to the fact that ...
-
Chapter and Conference Paper
Predefined-Time Event-Triggered Consensus for Nonlinear Multi-Agent Systems with Uncertain Parameter
In this paper, a novel predefined-time event-triggered control method is proposed, which achieved to the consistency of multi-agent systems with uncertain parameter. Firstly, a new predefined-time stability th...
-
Chapter and Conference Paper
Retrievable Image Encryption Based on Adaptive Block Compressed Sensing
The increasing popularity of the internet and mobile devices, cloud storage has emerged as a popular storage method. However, because data carries a lot of information, untrustworthy servers can access users’ ...
-
Chapter and Conference Paper
Normative Prior Network for Anomaly Segmentation in Retinal OCT Images
Anomaly segmentation refers to leveraging only normal images for model training to detect pixel-level anomalies in abnormal images in test phase, which gets rid of the reliance on expensive manual labels and i...
-
Chapter and Conference Paper
Spatial-Spectral Siamese and Similarity Network for Hyperspectral Image Classification
Recently, depth methods have developed rapidly and achieved remarkable achievements in the field of hyperspectral image classification. Deep learning largely depends on high-quality labels. However, for hypers...
-
Chapter and Conference Paper
Vision Transformer with Depth Auxiliary Information for Face Anti-spoofing
Face anti-spoofing (FAS) is an important part of the face recognition system. Although methods based on convolutional neural networks (CNN) have achieved great success, CNN may not be able to make good use of ...
-
Chapter and Conference Paper
Graph Spatial-Spectral Deep Subspace Clustering for Hyperspectral Image Classification
Deep subspace clustering (DSC) has become a research hotspot and achieved considerable success in unsupervised hyperspectral image (HSI) classification domain. However, previous researches seldom consider glob...
-
Chapter and Conference Paper
Joint Learning Based on Discriminant Representation and Group Collaborative Measurement for Image Set Classification
In daily life, it is easy to obtain a large number of images in the form of sets. How to extract discriminative information from a wide range of images become very important. Most of the existing image set cla...
-
Chapter and Conference Paper
Attention-Aware U-Net Network for Segmentation of Retinopathy Region
The important function of the computer-aided analysis platform for OCT (Optical Coherence Tomography) retinal images is image segmentation and the accuracy of the segmentation results affects the diagnosis of ...
-
Chapter and Conference Paper
Semi-supervised Generative Adversarial Network for Face Anti-spoofing
For the sake of safety, face recognition system often needs to include face anti-spoofing function and it has become one of the most popular topics nowadays. Traditional face anti-spoofing algorithms tend to c...
-
Chapter and Conference Paper
3D Vision Transformer for Postoperative Recurrence Risk Prediction of Liver Cancer
Hepatocellular carcinoma (HCC) is a kind of malignant tumor with a high fatality rate, and it has a serious impact on the patient’s normal life. Although the diagnostic scheme for liver cancer has been gradual...
-
Chapter and Conference Paper
Unsupervised Domain Adaptation with Self-selected Active Learning for Cross-domain OCT Image Segmentation
Segmentation of optical coherence tomography (OCT) images of retinal tissue has become an important task for the diagnosis and management of eye diseases. Deep convolutional neural networks have shown great su...
-
Chapter and Conference Paper
AFLLC: A Novel Active Contour Model Based on Adaptive Fractional Order Differentiation and Local-Linearly Constrained Bias Field
In this work, we propose a novel active contour model based on adaptive fractional order differentiation and the local-linearly constrained bias field for co** with images caused by complex intensity inhomog...
