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Chapter and Conference Paper
Time-Series Forecasting Through Contrastive Learning with a Two-Dimensional Self-attention Mechanism
Contrastive learning methods have impressive capabilities in time-series representation; however, challenges in capturing contextual consistency and extracting features that meet the requirements of representa...
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Chapter and Conference Paper
LMConvMorph: Large Kernel Modern Hierarchical Convolutional Model for Unsupervised Medical Image Registration
Medical image registration is a crucial task for numerous medical applications, such as radiation therapy planning and surgical navigation. While deep learning methods have shown promise in improving registrat...
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Chapter and Conference Paper
Trajectory Optimization for UAV-Aided Data Collections
The application of the unmanned aerial vehicles (UAV) in future wireless networks is getting more and more popular. This article investigates the flight trajectory optimization problem with minimum energy cons...
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Chapter and Conference Paper
A Surface Fitting Image Super-Resolution Algorithm Based on Triangle Mesh Partition
High-frequency information such as image edges and textures have an important influence on the visual effect of the super-resolution images. Therefore, it is vital to maintain the edge and texture features of ...
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Chapter and Conference Paper
BIDGAN: Blind Image Deblurring with Improved CycleGAN and Frequency Filtering
The details of images can be severely impaired when they are captured in motion . To overcome such a blind image deblurring problem, we propose a deblurring method based on improved CycleGAN. This method can r...
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Chapter and Conference Paper
Context-Aware Virtual Adversarial Training for Anatomically-Plausible Segmentation
Despite their outstanding accuracy, semi-supervised segmentation methods based on deep neural networks can still yield predictions that are considered anatomically impossible by clinicians, for instance, conta...
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Chapter and Conference Paper
Cyclic DenseNet for Tumor Detection and Identification
How to correctly and efficiently detect and identify tumors has always been a core issue in the medical field. In order to improve the accuracy and efficiency of tumor detection, we proposed a DenseNet-based t...
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Chapter and Conference Paper
Stock Prediction Model Based on Wavelet Packet Transform and Improved Neural Network
With the advent of the era of big data, the network’s intervention in the stock market has deepened and the security of the stock market has been seriously threatened. In order to maintain the security of the ...
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Chapter and Conference Paper
Modeling and Analysis Brain Development via Discriminative Dictionary Learning
Research on modeling and exploring of the normal brain maturity, such as in vivo study of the anatomy of the develo** brain, can provide references for developmental pathologies. In this paper, we model and ...
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Chapter and Conference Paper
Brain Status Prediction with Non-negative Projective Dictionary Learning
Study on brain status prediction has recently received increasing attention from the research community. In this paper, we propose to tackle brain status prediction by learning a discriminative representation ...
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Chapter and Conference Paper
Assumption Queries Processing of Probabilistic Relational Databases
Many prevail applications, such as data cleaning, sensor networks, tracking moving objects, emerge an increasing demand for managing uncertain data. Probabilistic relational databases support uncertain data ma...
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Chapter and Conference Paper
Correcting Wrongly Determined Opinions of Agents in Opinion Sharing Model
This paper aims at achieving a stable high accuracy of opinion sharing in a distributed network with the agents which have initial opinions. Specifically, the network is composed of multi-agents, and most agen...
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Chapter and Conference Paper
Research on the Algorithm of Converting Files Generated by CALPOST to AVS/Express Platform
The technology on visualizing the files generated by CALPOST efficiently and quickly is not so mature in environmental research. Based on the characteristic of the data stored in the CALPOST files, a CAL2AVS (...
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Chapter and Conference Paper
Query Optimization Strategies in Probabilistic Relational Databases
Most existing optimization strategies for relational algebra queries in probabilistic relational databases focus on accelerating probability computation of lineage expressions of answering tuples. However, non...
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Chapter and Conference Paper
Path Planning Methods for Auto-Guided Rice-Transplanters
Paddy field operation asks for robotization due to labor shortage. In this paper, a set of path planning methods were developed and tested on a guidance for transplanters. Path planning of fieldbody and headla...
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Chapter and Conference Paper
An Efficient Initialization Method for Probabilistic Relational Databases
Probabilistic relational databases play an important role on uncertain data management. Informally, a probabilistic database is a probability distribution over a set of deterministic databases (namely, possibl...
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Chapter and Conference Paper
Extraction of Feature Points on 3D Meshes Through Data Gravitation
Feature points are particularly simple elements which demonstrate a model efficiently and availably; nonetheless, the points on 3D models cannot be extracted completely yet. Therefore, we propose a new algorit...
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Chapter and Conference Paper
Image Interpolation Based on Weighted and Blended Rational Function
Conventional linear interpolation methods produce interpolated images with blurred edges, while edge directed interpolation methods make enlarged images with good quality edges but with details distortion for ...
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Chapter and Conference Paper
Initial Seeds Selection in Dynamic Clustering Method Based on Data Depth
Resorting to the theory of atomic models and the tool of data depth, we propose a novel method for initial seeds selection in dynamic clustering method. We define the cohesion of a point in a given data set, whic...
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Chapter and Conference Paper
Researches Based on Subject-Oriented Security in the Cyber-Physical System
The security research of Cyber-physical system is a dynamic development process. Because no single technique could ensure the absolute safety of CPS, so its safety problem must be considered from the overall a...