11,912 Result(s)
within
Chapter
**ao** Xu
Computer Science
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Chapter and Conference Paper
GaussTS: Towards Time Series Data Management in OpenGauss
The rapid advancement of sensor technology presents novel challenges in the efficient management of large scale time series data. In this demo, we demonstrate a time series data management module named GaussTS...
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Chapter and Conference Paper
Empowering Work-Life Harmony: Introducing a Porsche-Inspired Voice Digital Assistants Tailored for Women
With the rapid increase in the personalized demands for in-car voice assistants in the Generation Z era, innovation in digital assistants (DA) becomes crucial to better meet the growing needs of human-vehicle ...
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Chapter and Conference Paper
A Weakly Supervised Learning Method for Recognizing Childhood Tic Disorders
So far, the number of individuals with Tic disorder worldwide has reached 59 million, and the prevalence of the disorder is rapidly increasing globally. In this work, we focus on weakly supervised learning met...
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Chapter and Conference Paper
Prompting Generative Language Model with Guiding Augmentation for Aspect Sentiment Triplet Extraction
Aspect Sentiment Triplet Extraction (ASTE) is a challenging task in natural language processing concerning the automatic extraction of (aspect term, opinion term, sentiment polarity) triplets from a given text. C...
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Chapter and Conference Paper
Ensemble Deep Learning Approaches for Myopic Maculopathy Plus Lesions Segmentation
Myopia is a leading cause of visual impairment and blindness in several countries. Effective diagnosis and intervention are crucial, typically relying on manual image analysis by ophthalmologists, which is tim...
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Chapter and Conference Paper
Edible Oil Price Forecasting: A Novel Approach with Group Temporal Convolutional Network and BetaAdaptiveAdam
Edible oil, a fundamental food commodity, plays a pivotal role in the economic progression of a nation. The precise forecasting of edible oil prices is of utmost significance to a broad spectrum of stakeholder...
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Chapter and Conference Paper
Fourier-Based Instance Selective Whitening for Domain Generalized Lane Detection
Lane detection represents a fundamental task within autonomous driving. While deep learning has made remarkable advancements in the source domain, its ability to generalize to unseen target domains still poses...
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Chapter and Conference Paper
Feature Implicit Enhancement via Super-Resolution for Small Object Detection
In recent years, object detection has made significant strides due to advancements in deep convolutional neural networks. However, the detection performance for small objects remains challenging. The visual in...
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Chapter and Conference Paper
Make Spoken Document Readable: Leveraging Graph Attention Networks for Chinese Document-Level Spoken-to-Written Simplification
As people use language differently when speaking compared to writing, transcriptions generated by automatic speech recognition systems can be difficult to read. While techniques exist to simplify spoken langua...
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Chapter and Conference Paper
Visualization of Tumor Treatment Methods Based on Clustering Algorithms
The purpose of the article is to analyze the research hotspots and trends in tumor treatments using clustering algorithms such as LSI, LLR, Mutual Information and Kleinberg’s algorithm. The related articles of...
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Chapter and Conference Paper
Stepwise Change and Refine Network for Human Pose Transfer
Achieving person image synthesis through pose guidance is an arduous and profound endeavor. Addressing the limitations of previous approaches, namely inaccurate pose generation and inconsistencies with the tar...
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Chapter and Conference Paper
Time-Aware Preference Recommendation Based on Behavior Sequence
Sequential recommendation (SR) has become an important schema to assist people in rapidly finding their interest in the progressively growing data. Especially, long and short-term based methods capture user pr...
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Chapter and Conference Paper
SmartBuoy: A Machine Learning-Based Detection Method for Interest Flooding Attacks in VNDN
Due to the advantages of multi-source, multi-path, and in-network caching, Named Data Networking (NDN) can improve the efficiency of data exchange in Vehicular Ad-hoc NETworks (VANETs). As Vehicular Named Data...
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Chapter and Conference Paper
Salient Feature Enhanced Multi-object Tracking with Soft-Sparse Attention in Transformer
Most existing transformer-based Multi-object tracking (MOT) methods use Convolutional Neural Network (CNN) to extract features and then use a transformer to detect and track objects. However, feature extract n...
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Chapter and Conference Paper
Cross Domain Pulmonary Nodule Detection Without Source Data
The model performance on cross-domain pulmonary nodule detection usually degrades because of the significant shift in data distributions and the scarcity of annotated medical data in the test scenarios. Curren...
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Chapter and Conference Paper
Verifiable Secure Aggregation Protocol Under Federated Learning
Federated learning is a new machine learning paradigm used for collaborative training models among multiple devices. In federated learning, multiple clients participate in model training locally and use decent...
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Chapter and Conference Paper
Research on Cost Optimization of UAV Network Routing Protocol Based on OLSR Protocol
The HELLO message stands as the foundational and pivotal message structure within the OLSR protocol. It encompasses vital information, including neighbor types, primary addresses, and link state details concer...
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Chapter and Conference Paper
Exploring Cross-Modal Inconsistency in Entities and Emotions for Multimodal Fake News Detection
The automatic detection of multimodal fake news has attracted significant attention recently. Numerous existing methods focus on the fusion of unimodal features to generate multimodal news representations. How...
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Chapter and Conference Paper
Exploring the Effectiveness of Student Behavior in Prerequisite Relation Discovery for Concepts
What knowledge should a student grasp before beginning a new MOOC course? To answer this question, it is essential to automatically discover prerequisite relations among course concepts. Although researchers h...
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Chapter and Conference Paper
Fault Tolerance Aware Virtual Machine Scheduling Algorithm in Cloud Data Center Environment
Virtual machine (VM) scheduling is a complex problem in cloud environments, especially when reliability is considered. However, most of existing related works ignore the influence of this point. Therefore, thi...
