316 Result(s)
within
English
Machine Learning
**ze Shen
Chapter
Conference Paper
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Chapter and Conference Paper
Intrusion Detection Using Temporal Convolutional Networks
Intrusion detection system is an important network security facility. With the fast development of information technology, the information security is getting more serious. On the other side, making the IT equ...
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Chapter and Conference Paper
Adversarial Domain Adaptation for Chinese Semantic Dependency Graph Parsing
The Chinese Semantic Dependency Graph (CSDG) Parsing reveals the deep and fine-grained semantic relationship of Chinese sentences, and the parsing results have a great help to the downstream NLP tasks. However...
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Chapter and Conference Paper
Learnable Gabor Convolutional Networks
Commonly used convolutional operation does not have the ability to learn invariant information of images. However, some handcrafted image feature extractors, like Gabor wavelets, are robust to object’s scale ...
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Chapter and Conference Paper
Massive-Scale Models of Urban Infrastructure and Populations
As the world becomes more dense, connected, and complex, it is increasingly difficult to answer “what-if” questions about our cities and populations. Most modeling and simulation tools struggle with scale and ...
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Chapter and Conference Paper
Robust Segmentation of Nucleus in Histopathology Images via Mask R-CNN
Nuclei segmentation plays an import role in histopathology images analysis. Deep learning approaches have shown its strength for histopathology images processing in various studies. In this paper, we proposed ...
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Chapter and Conference Paper
Automatic Brain Tumor Segmentation with Domain Adaptation
Deep convolution neural networks, in particular, the encoder-decoder networks, have been extensively used in image segmentation. We develop a deep learning approach for tumor segmentation by combining a modifi...
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Chapter and Conference Paper
An Expert Validation Framework for Improving the Quality of Crowdsourced Clustering
Crowdclustering is a cost-effective mechanism that learns a cluster structure from data and crowdsourced human pairwise labels. Though some initial efforts have shown some effectiveness of crowdclustering, per...
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Chapter and Conference Paper
Dynamic Placement Algorithm for Multiple Classes of Mobile Base Stations in Public Safety Networks
As new mobile base stations (mBSs) have been constantly developed with various capacities, mobile coverage, and mobility models, the level of heterogeneity in public safety networks (PSNs) has been increasing
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Chapter and Conference Paper
A Hybrid Chain Based Incentive Mechanism for Resource Leasing in NDN
Since the main feature of Named Data Network (NDN) is in-net caching, it is crucial to motivate users to offer resource such as bandwidth and storage. However, few research works on incentive mechanism design ...
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Chapter and Conference Paper
Correction to: Single Image Super-Resolution via a Holistic Attention Network
In the originally published version of chapter 12, the first affiliation stated a wrong city and country. This has been corrected.
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Chapter and Conference Paper
Joint Extraction of Entity and Semantic Relation Using Encoder - Decoder Model Based on Attention Mechanism
Attention-based encoder-decoder neural network models have recently shown promising results in machine translation and speech recognition. In this work, we propose an attention based neural network model for j...
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Chapter and Conference Paper
DDU-Nets: Distributed Dense Model for 3D MRI Brain Tumor Segmentation
Segmentation of brain tumors and their subregions remains a challenging task due to their weak features and deformable shapes. In this paper, three patterns (cross-skip, skip-1 and skip-2) of distributed dense...
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Chapter and Conference Paper
Wind Turbine Clutter Suppression for Weather Radar Using Improved Ridge Regression Approach
The problem of clutter suppression is gaining importance because of many disadvantages. However, conventional clutter suppression methods cannot eliminate the great disturbances to radar system caused by wind ...
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Chapter and Conference Paper
Traffic Anomaly Detection for Data Communication Networks
The detection efficiency of the traditional data communication network traffic anomaly detection algorithm is low. And it is impossible to guarantee the accuracy of traffic detection in actual applications. T...
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Chapter and Conference Paper
DPAST-RNN: A Dual-Phase Attention-Based Recurrent Neural Network Using Spatiotemporal LSTMs for Time Series Prediction
For time series forecasting, the weight distribution among multivariables and the long-short-term time dependence are always very important and challenging. Traditional machine forecasting can’t automatically ...
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Chapter and Conference Paper
Split and Merge: Component Based Segmentation Network for Text Detection
This paper presents a novel component-based detector to locate scene texts with arbitrary orientations, shapes and lengths. Our approach detects text by predicting four components like text region (TR), text s...
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Chapter and Conference Paper
Underwater Enhancement Model via Reverse Dark Channel Prior
The interference of suspended particles causes the problems of color distortion, haze effect and visibility reduction in complex underwater environment. However, existing methods for enhancement often result i...
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Chapter and Conference Paper
Domain Adaptation for Eye Segmentation
Domain adaptation (DA) has been widely investigated as a framework to alleviate the laborious task of data annotation for image segmentation. Most DA investigations operate under the unsupervised domain adapt...
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Chapter and Conference Paper
Attention-Guided Deep Domain Adaptation for Brain Dementia Identification with Multi-site Neuroimaging Data
Deep learning has demonstrated its superiority in automated identification of brain dementia based on neuroimaging data, such as structural MRIs. Previous methods typically assume that multi-site data are samp...
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Chapter and Conference Paper
Reconstruction and Re-ranking: A Simple and Effective Approach for Question Answering
With the rapid growth of knowledge bases (KBs), question answering over knowledge base, a.k.a. KBQA has drawn huge attention in recent years. Most of the existing methods follow the simply matching method and ...
