25 Result(s)
within
Yu. Li
Computer Science
Artificial Intelligence
Image Processing and Computer Vision
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Article
Open AccessJoint optic disc and cup segmentation based on multi-scale feature analysis and attention pyramid architecture for glaucoma screening
Automatic segmentation of optic disc (OD) and optic cup (OC) is an essential task for analysing colour fundus images. In clinical practice, accurate OD and OC segmentation assist ophthalmologists in diagnosing...
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Article
Semantic segmentation network with multi-path structure, attention reweighting and multi-scale encoding
Semantic segmentation is an active field of computer vision. It provides semantic information for many applications. In semantic segmentation tasks, spatial information, context information, and high-level sem...
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Chapter and Conference Paper
Tiny-YOLOv7: Tiny Object Detection Model for Drone Imagery
With the rapid development of drones, tiny object detection in drone-captured scenarios has become a challenge task. However, the altitude of the drone changes while flying lead to the scale of the object chan...
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Article
Hybrid War** Fusion for Video Frame Interpolation
Video frame interpolation aims to synthesize new intermediate frames between existing ones, which is an important task in video enhancement. A classic direction in this field is flow-based which estimates moti...
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Chapter and Conference Paper
A Novel Dual-Modal Biometric Recognition Method Based on Weighted Joint Group Sparse Representation Classification
Multi-modal biometric recognition technology is an effective method to improve the accuracy and reliability of identity recognition. However, there are some problems (such as feature space incompatibility) wit...
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Chapter and Conference Paper
A Finger Bimodal Fusion Algorithm Based on Improved Densenet
Compared with single-mode biometric recognition, multimodal biometric recognition has been widely used because of its high security and high accuracy. Among them, finger based multimodal biometric recognition ...
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Chapter and Conference Paper
Self-paced Safe Co-training for Regression
In semi-supervised learning, co-training is successfully in augmenting the training data with predicted pseudo-labels. With two independently trained regressors, a co-trainer iteratively exchanges their select...
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Article
Attention Guided Low-Light Image Enhancement with a Large Scale Low-Light Simulation Dataset
Low-light image enhancement is challenging in that it needs to consider not only brightness recovery but also complex issues like color distortion and noise, which usually hide in the dark. Simply adjusting th...
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Chapter and Conference Paper
Learning Infant Brain Developmental Connectivity for Cognitive Score Prediction
During infancy, the human brain develops rapidly in terms of structure, function and cognition. The tight connection between cognitive skills and brain morphology motivates us to focus on individual level cogn...
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Chapter and Conference Paper
Research on Chinese Word Segmentation Based on Conditional Random Fields
Word segmentation is the first step in Chinese natural language processing. The accuracy of segmentation has substantial impacts on subsequent tasks such as part-of-speech tagging, semantic analysis, etc. This...
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Chapter and Conference Paper
Chinese Word Sense Disambiguation Based on Classification
Word sense disambiguation (WSD) is a well-known task in the field of natural language processing. It attempts to determine a meaning of a word that has a couple of senses. This paper studies the Chinese word s...
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Chapter and Conference Paper
Research on the Authorship of Dream of the Red Chamber Based on Link Prediction
Dream of the Red Chamber (DRC), written in Qing dynasty, is a prestigious classical novel in Chinese literature. There exists a disputation over the authorship of DRC for the last 40 chapters. This research ma...
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Chapter and Conference Paper
L2R-QA: An Open-Domain Question Answering Framework
Open-domain question answering has always being a challenging task. It involves information retrieval, natural language processing, machine learning, and so on. In this work, we try to explore some comparable ...
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Chapter and Conference Paper
An Advanced Least Squares Twin Multi-class Classification Support Vector Machine for Few-Shot Classification
In classification tasks, deep learning methods yield high performance. However, owing to lack of enough annotated data, deep learning methods often underperformed. Therefore, we propose an advance version of l...
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Chapter and Conference Paper
Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach
Biomarkers are not well understood in depression, partly because there is no golden rule of what is abnormal in which patients and how neurobiological information can be used to improve diagnosis. The heteroge...
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Chapter and Conference Paper
Data Augmentation for Deep Learning of Judgment Documents
With the increasing number of machine learning parameters, the requirements on data quantity are getting higher and higher to train a good model. The choice of methods and the optimization of parameters can im...
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Chapter and Conference Paper
Using Case Facts to Predict Penalty with Deep Learning
With the promotion of Wisdom Court construction and the increasing completeness of judicial big data, the combination of judicial and artificial intelligence attracted more and more attention. The Judicial doc...
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Chapter and Conference Paper
Adaptive Flower Pollination Algorithm Based on Chaotic Map
Flower pollination algorithm (FPA) is one of the well-known evolutionary techniques used extensively to solve optimization problems. Despite its efficiency and wide use, the identical search behaviors may lead...
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Chapter and Conference Paper
Fault Diagnosis Method of Diesel Engine Based on Improved Structure Preserving and K-NN Algorithm
The diesel engine fault data is nonlinear and it’s difficult to extract the characteristic information. Kernel Principal Component Analysis (KPCA) is used to extract features of nonlinear data, only considerin...
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Chapter and Conference Paper
A New Scheme for QoE Management of Live Video Streaming in Cloud Environment
Live video streaming process consumes very large data storage and takes very long time, so it requires big data storage and computing infrastructures for implementation. Accordingly, the use of cloud computing...
