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Extreme weather recognition using GoogLeNet can achieve excellent performance, which is far superior to the conventional methods. However, the complexity of GoogLeNet is relatively high. Furthermore, for the small scale data, GoogLeNet usually cannot achieve the performance as the large scale data does. In this paper, a novel dual fine-tuning strategy is proposed to train the GoogLeNet model. Firstly,...
In cognitive radio network (CRN), secondary users (SUs) suffer from the spectrum sensing data falsification (SSDF) attack launched by malicious users (MUs). To deal with SSDF attack, one of the typical artificial neural networks (ANN): self-organizing map (SOM) neural network is recommended. SOM network possesses the ability of classifying the SUs into categories with different frequency of occurrence...
The influence of temperature, irradiance and shielding ratio on the output characteristic curve of photovoltaic cells was studied in this paper. In order to improve the photoelectric conversion efficiency of photovoltaic cells, combining three major factors that affect photovoltaic cells, a maximum power point tracking (MPPT) scheme based on large variation genetic algorithm was proposed. In this...
This paper presents a novel unsupervised domain adaptation method for cross-domain visual recognition. We propose a unified framework that reduces the shift between domains both statistically and geometrically, referred to as Joint Geometrical and Statistical Alignment (JGSA). Specifically, we learn two coupled projections that project the source domain and target domain data into low-dimensional...
The task of person re-identification (re-id) is to match images of people observed in different camera views. Recent researches mainly focus on feature representation and metric learning. Many global metric learning approaches have achieved good performance. Since comparing all of the samples with a single global metric is inappropriate to handle heterogeneous data, some local metric learning approaches...
The Fine-grained Vehicle recognition is easily affected by small visual changes. The existing recognition methods have less robustness to these conditions (such as illumination, weather changes, etc.) and the accuracy of vehicle recognition in complex environments cannot achieve a satisfying result. In this paper, a high-accuracy fine-grained vehicle recognition method using Convolutional Neural Network...
Sparse Representation-based Classifier (SRC) is less sensitive to the shortage of data and the selection of feature space. In this paper, SRC is adopted to perform automatic analysis of tongue substance color and coating color which is considered as small dataset classification task. Firstly, for both training samples and testing samples, the tongue body regions are segmented, the regions of tongue...
Hyperspectral image (HIS) classification is a hot topic in remote sensing community and most of the existing methods extract the features of original Hyperspectral data using shallow layer networks such as neural network (NN) and support vector machine (SVM). As deep learning recently achieves great success in machine learning and pattern recognition area for its ability in deep feature extraction...
Considering the fact that pornographic images are flooding on the web, we propose a pornographic image recognition method based on convolutional neural network. This method can be divided into two parts: coarse detection and fine detection. Because majority of images are normal, we use coarse detecting to quickly identify the normal images with no or fewer skin-color regions and facial images. For...
For multiuser massive MIMO systems, the acquisition and utilization of statistical channel information is very important. In this paper, we first adopt PASTd algorithm to track the uplink dominant eigenvectors (sub-eigenspace) of channel covariance matrix and then present a low-complexity algorithm to transform the uplink eigenvectors to the downlink eigenvectors. Thirdly, two scheduling algorithms...
The important task of correcting label noise is addressed infrequently in literature. The difficulty of developing a robust label correction algorithm leads to this silence concerning label correction. To break the silence, we propose two algorithms to correct label noise. One utilizes self-training to re-label noise, called Self-Training Correction (STC). Another is a clustering-based method, which...
In order to meet the special control requests of an intercept missile, a new boost-phase guidance law is proposed based on the theory of pesudospcetral method and artificial neural network. A group of optimal trajectories with multiple constraints, obtained by hp-adaptive pesudospcetral method, is used as samples to train the neural network. To show the effect of training patterns on the guidance...
Sentiment lexicon is the core of many academic and commercial sentiment analysis system. But compared with the plentiful English sentiment resources, Chinese sentiment lexicon is scarce which limits the application of lexicon-based method in Chinese sentiment analysis.
A compressed pornographic image recognition method is proposed by using incremental learning. For describing pornographic image, visual words are created from low-resolution (LR) image reconstructed from the compressed stream of the pornographic image. Covering algorithm is utilized to train and recognize the visual words in order to build the initial classification model of pornographic image. At...
In this paper, the Bayesian Cramér-Rao lower bounds (BCRBs) on dynamic individual channel estimation is examined in an amplify-and-forward (AF) one-way relay network (OWRN) under time selective flat fading channel scenario, where the superimposed training framework is adopted. The target of our work is to formulate the nonlinear dynamic state-space equation for individual channels and derive the online/offline...
In this paper, a modified CRF algorithm is proposed for recognition of vision-based dynamic hand gestures. This algorithm abandons the condition necessary for Hidden Markov Models that the action sequences must be independent. And dynamic hand gestures are classified by some most representative segments (MRSs) rather than the full gestures themselves. First, the Longest Common Sequence (LCS) is employed...
Parameters selection of support vector machine (SVM) is a key problem in the application of SVM, which has influence on generalization performance of SVM. The commonly used method, grid search (GS), is time-consuming especially for very large dataset. By using coarse grid search and pattern search (PS) to select kernel parameters and penalty factor, a fast method of parameters selection of SVM based...
The nodules and the multiple times larger non-nodules of the regions of interested(ROIs) in lung areas are achieved, that would lead to a serious imbalance on the sample data. Many scholars have proposed some algorithms to solve this problem. In this paper, in order to guarantee that there is no correlation among the extracted characteristics, the PCA method is adopted to optimize and reduce dimensions,...
Inspired by the self-protection mechanism of nature immune system, a spam short message filtering algorithm is proposed based on artificial immune system. The algorithm principle and process is given, the conception of affinity, antigen-antibody is introducted. The variability of antibody in time makes the system has a good dynamic performance and adaptability. the feasibility and effectiveness of...
In order to analyze the data rationally in the process of teaching study, some statistical methods are used in this paper. By introducing descriptive statistics, parametric hypothesis test, one-way analysis of variances (ANOVA) and correlation analysis, the problem of data analysis in practice can be rationally solved. For illustration, some practical cases are utilized. And the result shows that...
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