17 Result(s)
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Chapter and Conference Paper
Learning Local Feature Descriptors with Quadruplet Ranking Loss
In this work, we propose a novel deep convolutional neural network (CNN) with quadruplet ranking loss to learn local feature descriptors. The proposed model receives quadruplets of two corresponding patches an...
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Chapter and Conference Paper
Finding Frequent Items in Time Decayed Data Streams
Identifying frequently occurring items is a basic building block in many data stream applications. A great deal of work for efficiently identifying frequent items has been studied on the landmark and sliding w...
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Chapter and Conference Paper
Improving Semi-supervised Text Classification by Using Wikipedia Knowledge
Semi-supervised text classification uses both labeled and unlabeled data to construct classifiers. The key issue is how to utilize the unlabeled data. Clustering based classification method outperforms other s...
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Chapter and Conference Paper
OptRegion: Finding Optimal Region for Bichromatic Reverse Nearest Neighbors
The MaxBRNN problem is to find an optimal region such that setting up a new service site within this region might attract the maximal number of customers by proximity. It has many practical applications such a...
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Chapter and Conference Paper
A Technique for Improving the Performance of Naive Bayes Text Classification
Naive Bayes classifier is widely used in text classification tasks, and it can perform surprisingly well, it is often regarded as a baseline. But previous researches show that the skewed distribution of traini...
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Chapter and Conference Paper
Composition Based Semantic Scene Retrieval for Ancient Murals
Retrieval of similar scenes in ancient murals research is an important but time-consuming job for researchers. However, content-based image retrieval (CBIR) systems cannot fully deal with such issues since the...
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Chapter
Large Area Interactive Browsing for High Resolution Digitized Dunhuang Murals
The Dunhuang Motao Grottoes consist of about 45000 square meters murals, which are the most important part of the Dunhuang Art. As Dunhuang murals are rich in contents, large in sizes and amounts, high resolut...
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Chapter and Conference Paper
Multi-projector Calibration and Alignment Using Flatness Analysis for Irregular-Shape Surfaces
A multi-projector calibration and alignment method, which has no assumptions on projection surfaces’ shape, is presented. Based on surface flatness analysis, the method will automatically partition the project...
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Chapter and Conference Paper
An Ultra Large Area Scanner for Ancient Painting and Calligraphy
It is of great significance to digitize ancient paintings and calligraphy, especially for a country with five thousand years of history and rich cultural heritages. Millions of paintings and calligraphy are ha...
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Chapter and Conference Paper
Color Changing and Fading Simulation for Frescoes Based on Empirical Knowledge from Artists
Visualizing the color changing and fading process of ancient Chinese wall paintings to tourists and researchers is of great value in both education and preservation. But previously, because empirical knowledge...
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Chapter and Conference Paper
Style Strokes Extraction Based on Color and Shape Information
Taking Dunhuang MoGao Frescoes as research background, a new algorithm to extract style strokes from fresco images is proposed. All the pixels in a fresco image are classified into either the stroke objects or...
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Chapter and Conference Paper
Worm Traffic Modeling for Network Performance Analysis
Worm research depends on simulation to a large degree due to worm propagation characters. In worm simulation, worm traffic generation is the base to analyze influences of worm traffic on network. The popular R...
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Chapter and Conference Paper
A Novel Mechanism to Defend Against Low-Rate Denial-of-Service Attacks
Low-rate TCP-targeted Denial-of-Service (DoS) attack (shrew) is a new kind of DoS attack which is based on TCP’s Retransmission Timeout (RTO) mechanism and can severely reduce the throughput of TCP traffic on ...
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Chapter and Conference Paper
The Multi-fractal Nature of Worm and Normal Traffic at Individual Source Level
Worms have been becoming a serious threat in web age because worms can cause huge loss due to the fast-spread property. To detect worms effectively, it is important to investigate the characteristics of worm t...
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Chapter and Conference Paper
A CATV and Internet Combined Framework for Distance Learning
Web based learning enables more students to have a chance to access the distance learning resources. However, the early experience of using this new learning method in China exposes a few problems, among which...
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Chapter and Conference Paper
Research of Characteristics of Worm Traffic
Worm is becoming a more and more serious issue because worm attacks can cause huge loss in short time due to the fast-spreading character. When breaking out, worms induce abnormal traffic unlike the normal tra...
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Chapter and Conference Paper
FatNemo: Building a Resilient Multi-source Multicast Fat-Tree
This paper proposes the idea of emulating fat-trees in overlays for multi-source multicast applications. Fat-trees are like real trees in that their branches become thicker the closer one gets to the root, thu...
