Yankui Sun
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View article: ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation
ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation Open
Vision-language pre-training (VLP) methods are blossoming recently, and its crucial goal is to jointly learn visual and textual features via a transformer-based architecture, demonstrating promising improvements on a variety of vision-lang…
View article: Image classification using convolutional neural network with wavelet domain inputs
Image classification using convolutional neural network with wavelet domain inputs Open
Commonly used convolutional neural networks (CNNs) usually compress high‐resolution input images. Although it reduces the computation requirements into a reasonable range, the downsampling operation causes information loss, which affects t…
View article: Automatic diagnosis of macular diseases from OCT volume based on its two-dimensional feature map and convolutional neural network with attention mechanism
Automatic diagnosis of macular diseases from OCT volume based on its two-dimensional feature map and convolutional neural network with attention mechanism Open
We present a general framework of OCT volume classification based on its 2-D feature map and CNN with attention mechanism and describe its implementation schemes. Our proposed methods could classify OCT volumes automatically and effectivel…
View article: MDAN-UNet: Multi-Scale and Dual Attention Enhanced Nested U-Net Architecture for Segmentation of Optical Coherence Tomography Images
MDAN-UNet: Multi-Scale and Dual Attention Enhanced Nested U-Net Architecture for Segmentation of Optical Coherence Tomography Images Open
Optical coherence tomography (OCT) is an optical high-resolution imaging technique for ophthalmic diagnosis. In this paper, we take advantages of multi-scale input, multi-scale side output and dual attention mechanism and present an enhanc…
View article: Automatic detection of retinal regions using fully convolutional networks for diagnosis of abnormal maculae in optical coherence tomography images
Automatic detection of retinal regions using fully convolutional networks for diagnosis of abnormal maculae in optical coherence tomography images Open
In conventional retinal region detection methods for optical coherence tomography (OCT) images, many parameters need to be set manually, which is often detrimental to their generalizability. We present a scheme to detect retinal regions ba…
View article: Optimized Deep Convolutional Neural Networks for Identification of Macular Diseases from Optical Coherence Tomography Images
Optimized Deep Convolutional Neural Networks for Identification of Macular Diseases from Optical Coherence Tomography Images Open
Finetuning pre-trained deep neural networks (DNN) delicately designed for large-scale natural images may not be suitable for medical images due to the intrinsic difference between the datasets. We propose a strategy to modify DNNs, which i…
View article: NFD: Toward Real-time Mining of Short-timescale Gravitational Microlensing Events
NFD: Toward Real-time Mining of Short-timescale Gravitational Microlensing Events Open
To search short-timescale microlensing (ML) events () from high-cadence, wide-field survey in real time, we present an algorithm called NFD (normalized feature deviation) to monitor all the observed light curves and to alert abnormal devia…
View article: Efficient Deep Learning-Based Automated Pathology Identification in Retinal Optical Coherence Tomography Images
Efficient Deep Learning-Based Automated Pathology Identification in Retinal Optical Coherence Tomography Images Open
We present an automatic method based on transfer learning for the identification of dry age-related macular degeneration (AMD) and diabetic macular edema (DME) from retinal optical coherence tomography (OCT) images. The algorithm aims to i…
View article: Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition
Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition Open
Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is a…
View article: Fully automated macular pathology detection in retina optical coherence tomography images using sparse coding and dictionary learning
Fully automated macular pathology detection in retina optical coherence tomography images using sparse coding and dictionary learning Open
We propose a framework for automated detection of dry age-related macular degeneration (AMD) and diabetic macular edema (DME) from retina optical coherence tomography (OCT) images, based on sparse coding and dictionary learning. The study …
View article: THE ‘MOON MAPPING’ PROJECT TO PROMOTE COOPERATION BETWEEN STUDENTS OF ITALY AND CHINA
THE ‘MOON MAPPING’ PROJECT TO PROMOTE COOPERATION BETWEEN STUDENTS OF ITALY AND CHINA Open
The research project ‘Moon Mapping’ has been established in 2014 between the Italian and Chinese Governments to promote cooperation and exchange between undergraduate students from both countries. The operational phase of the project start…
View article: 3D automatic segmentation method for retinal optical coherence tomography volume data using boundary surface enhancement
3D automatic segmentation method for retinal optical coherence tomography volume data using boundary surface enhancement Open
With the introduction of spectral-domain optical coherence tomography (SD-OCT), much larger image datasets are routinely acquired compared to what was possible using the previous generation of time-domain OCT. Thus, there is a critical nee…
View article: 3D Automatic Segmentation Method for Retinal Optical Coherence Tomography Volume Data Using Boundary Surface Enhancement
3D Automatic Segmentation Method for Retinal Optical Coherence Tomography Volume Data Using Boundary Surface Enhancement Open
With the introduction of spectral-domain optical coherence tomography (SDOCT), much larger image datasets are routinely acquired compared to what was possible using the previous generation of time-domain OCT. Thus, there is a critical need…