51 Result(s)
within
Chapter
Conference Paper
Yi**ang Chen
Computer Imaging, Vision, Pattern Recognition and Graphics
Information Systems and Communication Service
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Chapter and Conference Paper
PRGAN: A Progressive Refined GAN for Lesion Localization and Segmentation on High-Resolution Retinal Fundus Photography
Retinal-related diseases are the leading cause of vision loss and even blindness. The automatic methods for retinal disease segmentation based on medical images are essential for timely treatment. Fully superv...
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Chapter and Conference Paper
Visual Research and Predictive Analysis of Land Resource Use Type Change
Land cover change is a hot topic in the interdisciplinary research of global change and land science. The existing spatial visualization methods based on remote sensing images have the advantages of wide detec...
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Chapter and Conference Paper
Image Magnification Network for Vessel Segmentation in OCTA Images
Optical coherence tomography angiography (OCTA) is a novel non-invasive imaging modality that allows micron-level resolution to visualize the retinal microvasculature. The retinal vessel segmentation in OCTA i...
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Chapter and Conference Paper
Unpaired and Self-supervised Optical Coherence Tomography Angiography Super-Resolution
Optical coherence tomography angiography (OCTA) is usually used to observe the blood flow information of retina and choroid. It is meaningful for clinicians to observe more microvascular details by enhancing t...
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Chapter and Conference Paper
MultiGAN: Multi-domain Image Translation from OCT to OCTA
Optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) are important imaging techniques for assessing and managing retinal diseases. OCTA can display more blood vessel informati...
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Chapter and Conference Paper
EBANet: Efficient Boundary-Aware Network for RGB-D Semantic Segmentation
Semantic segmentation is widely used in robot perception and can be used for various subsequent tasks. Depth information has been proven to be a useful clue in the semantic segmentation of RGB-D images for pro...
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Chapter and Conference Paper
Information Lossless Multi-modal Image Generation for RGB-T Tracking
Visible-Thermal infrared(RGB-T) multimodal target representation is a key issue affecting RGB-T tracking performance. It is difficult to train a RGB-T fusion tracker in an end-to-end way, due to the lack of an...
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Chapter and Conference Paper
HotLT: LT Code-Based Secure and Reliable Consortium Blockchain Storage Systems
The consortium blockchain is deployed in many key industries because decentralization is irreversible and traceable. However, the storage system of the alliance chain usually adopts a full copy method, which l...
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Chapter and Conference Paper
Unsupervised Medical Image Registration Based on Multi-scale Cascade Network
As a core technique of medical image analysis task, image registration is the process of finding the non-linear spatial correspondence among the input images. Comparing with supervised learning methods, unsupe...
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Chapter and Conference Paper
SETFF: A Semantic Enhanced Table Filling Framework for Joint Entity and Relation Extraction
In the study of text understanding and knowledge graph construction, the process of extracting entities and relations from unstructured text is crucial. Lately, joint extraction has achieved more significance ...
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Chapter and Conference Paper
ED-AnoNet: Elastic Distortion-Based Unsupervised Network for OCT Image Anomaly Detection
The use of anomaly detection methods based on the deep convolutional neural network has shown its success on optical coherence tomography (OCT) images. However, these methods only train normal samples from hea...
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Chapter and Conference Paper
Disentangled Contrastive Learning for Learning Robust Textual Representations
Although the self-supervised pre-training of transformer models has resulted in the revolutionizing of natural language processing (NLP) applications and the achievement of state-of-the-art results with regard...
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Chapter and Conference Paper
Rotation-DPeak: Improving Density Peaks Selection for Imbalanced Data
Density Peak (DPeak) is an effective clustering algorithm. It maps arbitrary dimensional data onto a 2-dimensional space, which yields cluster centers and outliers automatically distribute on upper right and u...
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Chapter and Conference Paper
Road Damage Detection and Classification Based on M2det
Road damage detection is very important for road maintenance. Deep learning is one of the popular method in road damage detection. Deep learning road damage detection methods include Fast R-CNN, Faster R-CNN, ...
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Chapter and Conference Paper
GVNP: Global Vectors for Node Representation
Learning low-dimensional embeddings of nodes in networks is an effective way to solve the network analytic problem, from traffic network to recommender systems. However, most existing approaches are inherently...
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Chapter and Conference Paper
Guided Deep Reinforcement Learning for Path Planning of Robotic Manipulators
To improve the efficiency of deep reinforcement learning (DRL)-based methods for robotic path planning in the unstructured environment with obstacles, we propose a Guided Deep Reinforcement Learning (GDRL) for...
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Chapter and Conference Paper
Exploiting Spatial-Spectral Feature for Hyperspectral Image Classification Based on 3-D CNN and Bi-LSTM
Hyperspectral remote sensing has been gaining more and more attention in recent years because of the rich spectral and spatial information contained in hyperspectral image (HSI). With the rapid development of ...
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Chapter and Conference Paper
Semantic Segmentation for Evaluation of Defects on Smartphone Screens
Smartphone recycling is a heated topic recently because of environmental and economical concerns. However, the limited recognition ability of naked eyes to find defects on phones impedes further growth of the ...
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Chapter and Conference Paper
ICPM: An Intelligent Compound Prediction Model Based on GA and GRNN
In order to reduce the prediction error of the heavy metal content of farmland soil by General Regression Neural Network (GRNN), an Intelligent Compound Prediction Model (ICPM) was proposed. As the result of G...
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Chapter and Conference Paper
Research on Military Application of Operating System for Internet of Things
IoT OS is the core content of IoT applications. In this paper, the development of IoT OS is firstly overviewed, and the characteristics of terminal and server IoT OS are contrasted. Then the status of the glob...
