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Chapter and Conference Paper
Semi-calibrated Near-Light Photometric Stereo
We tackle the nonlinear problem of photometric stereo under close-range pointwise sources, when the intensities of the sources are unknown (so-called semi-calibrated setup). A variational approach aiming at ro...
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Chapter and Conference Paper
A Data Stream Clustering Algorithm Based on Density and Extended Grid
Based on the traditional grid density clustering algorithm, proposing A Data Stream Clustering Algorithm Based on Density and Extended Grid(DEGDS). The algorithm combines the advantages of grid clustering algo...
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Chapter and Conference Paper
The Study on Grade Categorization Model of Question Based on on-Line Test Data
To tackle with the blindness of random questions choosing for exercise and test of the on-line learning system, this paper clusters questions exploiting various feature subsets and parameters via K-means. For...
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Chapter and Conference Paper
Identity Authentication Technology of Mobile Terminal Based on Cloud Face Recognition
The face recognition of mobile terminal plays an important role in the identity authentication technology. But there are some problems such as long detection time and low recognition rate due to the performanc...
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Chapter and Conference Paper
Gbest-Guided Covariance Matrix Adaptation Evolution Strategy for Large Scale Global Optimization
The optimization of a large number of decision variables, so called large scale global optimization (LSGO) remains challenging for existing heuristics. Inspired by the concept of global best (gbest) guided str...
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Chapter and Conference Paper
Color Two-Dimensional Principal Component Analysis for Face Recognition Based on Quaternion Model
The color two-dimensional principal component analysis (color 2DPCA) approach based on quaternion model is presented for color face recognition. Based on 2D quaternion matrices rather than 1D quaternion vector...
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Chapter and Conference Paper
2D Human Parsing with Deep Skin Model and Part-Based Model Inference
Human parsing plays an important role in action understanding, clothing recommendation and human-computer interaction, etc. However, variations of human pose, clothes, viewpoint and cluttered background make t...
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Chapter and Conference Paper
A Hashing Image Retrieval Method Based on Deep Learning and Local Feature Fusion
The multimedia information such as images and videos has been growing rapidly, how to efficiently retrieve large-scale image dataset to meet user needs is an urgent problem. The traditional method has the prob...
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Chapter and Conference Paper
Fully Combined Convolutional Network with Soft Cost Function for Traffic Scene Parsing
Autonomous car has achieved unprecedented improvement in object detection because of the high performance of deep convolutional neural networks, and now researches are devoted to more complex traffic scene par...
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Chapter and Conference Paper
Effects of Simulated Annealing Strategy on Swarm Intelligence Algorithm
Swarm intelligence algorithm (SI) is a kind of stochastic search algorithm based on swarm. Similar to other evolutionary algorithm, when solving the complicated multimodal problem using SI, it is easy to have ...
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Chapter and Conference Paper
An Efficient Conjunctive Keyword Searchable Encryption Scheme for Mobile Cloud Computing
The integration of the cloud and mobile device enables users more convenient to access, retrieve the file, but due to the limitations of resources of mobile devices, how to shorten the search time and get more...
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Chapter and Conference Paper
Two-Stage Flow-Open Shop Scheduling Problem to Minimize Makespan
This paper investigates a novel shop scheduling model, in which each job is processed first in a flow shop and then in an open shop. The objective is to optimize the maximum completion time, i.e. makespan. For...
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Chapter and Conference Paper
Yet Another Schatten Norm for Tensor Recovery
In this paper, we introduce a new class of Schatten norms for tensor recovery. In the new norm, unfoldings of a tensor along not only every single order but also all combinations of orders are taken into accou...
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Chapter and Conference Paper
A Swarm Intelligence Algorithm Inspired by Twitter
For many years, evolutionary computation researchers have been trying to extract the swarm intelligence from biological systems in nature. Series of algorithms proposed by imitating animals’ behaviours have es...
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Chapter and Conference Paper
Location Selection of Multiple Logistics Distribution Center Based on Particle Swarm Optimization
Distribution center is an important pivot position at the logistics system. This paper presents the site selection’s model of logistics distribution center based on decision matrix C, which adopts particle swarm ...
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Chapter and Conference Paper
Speech Denoising Based on Sparse Representation Algorithm
A new speech denoising method that aims for processing corrupted speech signal which is based on K-SVD sparse representation algorithm is proposed in this paper. Here, the DCT sparse and redundant representat...
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Chapter and Conference Paper
Incremental Robust Nonnegative Matrix Factorization for Object Tracking
Nonnegative Matrix Factorization (NMF) has received considerable attention in visual tracking. However noises and outliers are not tackled well due to Frobenius norm in NMF’s objective function. To address thi...
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Chapter and Conference Paper
A Note on the Guarantees of Total Variation Minimization
In this paper, we provide a simplified understanding of the guarantees of 1-dimension total variation minimization. We consider a slightly modified total variation minimization rather than the original one. T...
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Chapter and Conference Paper
Time Series Classification Based on Multi-codebook Important Time Subsequence Approximation Algorithm
This paper proposes a multi-codebook important time subsequence approximation (MCITSA) algorithm for time series classification. MCITSA generates a codebook using important time subsequences for each class bas...
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Chapter and Conference Paper
K-SVD Based Image Denoising Method Using Image Residual Information in Different Frequency Bands
The common image denoising methods only consider how to restore well image information from noise images, but neglect the effects of residual information between restored images and given images. To enhance de...