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This paper proposed a new Vehicle Make Recognition (VMR) method using the PCANet features extracted from vehicle front view images. The PCANet architecture processes every input vehicle image through only three very simple data processing components: cascaded principle component analysis (PCA), binary hashing, and block-wise histograms, and generates a sparse vector as the feature representation....
Word segmentation is the first step in Chinese natural language processing, and the error caused by word segmentation can be transmitted to the whole system. In order to reduce the impact of word segmentation and improve the overall performance of Chinese short text classification system, we propose a hybrid model of character-level and word-level features based on recurrent neural network (RNN) with...
The content-based image recognition is a research focus in the field of computer vision. Machine learning especially deep learning has a great potential in the field of image recognition. This paper adopts the support vector machine algorithm and deep learning method convolutional neural network to recognize books in the digital image library and compares their performance. Experiments show that both...
Wind ramps introduce significant uncertainty into wind power generation. Reliable system operation, however, requires accurate detection and forecast of wind ramps, especially at high penetration levels. In this paper, to deal with the wind ramp dynamics, a support vector machine (SVM)-enhanced Markov model is developed for short-term wind power forecast, based on one key observation from the measurement...
Resource prediction (e.g. CPU/memory utilization) of cloud computing jobs has attracted substantial amount of attention. Existing works use regression methods based on historical information of jobs, with an impractical assumption that the job to be predicted has the same class as the historical jobs. To address this problem, we propose to take the category of the jobs into consideration for effective...
Video caption extraction has become a very popular research area in the last few decades. Many reasons makes it a challenging task. A large number of techniques have been proposed to address this problem. This paper reviews the progress in this area and various methods towards different stages of text extraction in videos, and also discusses the promising direction of the future research.
Interactive genetic algorithms (IGAs) are effective methods of tackling optimization problems involving qualitative indices by incorporating a user's evaluations into traditional genetic algorithms. The problem of user fatigue resulting from the user's evaluations, however, has a negative influence on the performance of these algorithms. Substituting the user's evaluations with various surrogate models...
Electrocardiogram (ECG) reflects cardiac electrical activity, and varies from person to person, which could be used for biometrics identification. ECG biometrics identification algorithm is presented in this paper based on Matching Pursuit (MP) and Support Vector Machine (SVM). The ECG signal is decomposed into atoms by sparse decomposition with Gabor dictionary which contain ECG signal's important...
Neurotoxins can be divided into presynaptic neurotoxins and postsynaptic neurotoxins based on their mechanism of action. The two neurotoxins have important application in basic research and drug design. Presynaptic neurotoxins have been used for treatment of migraine headache and cerebral palsy. Therefore, the successful prediction of these two neurotoxins is becoming very important in recent years...
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