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This paper deals with the field of computer vision, mainly for the application of deep learning in object detection task. On the one hand, there is a simple summary of the datasets and deep learning algorithms commonly used in computer vision. On the other hand, a new dataset is built according to those commonly used datasets, and choose one of the network called faster r-cnn to work on this new dataset...
Text classification is the foundation and core of text mining. Naive Bayes is an effective method for text classification. This paper improves the accuracy of Naive Bayes classification using improved information gain, one of methods of feature extraction, by reducing the impact of low-frequency words. In this paper, we use a widely corpus of NLTK. According to the test results, The accuracy of the...
In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of in-game data makes the analytical task even more challenging...
The imbalanced data set has been reported to hinder the classification performance of many machine learning algorithms on both accuracy and speed. But extremely imbalanced data sets (3~5% positive samples) are common for many applications, such as multimedia semantic classification. In this paper, we propose a novel algorithm to automatically remove samples that have no or negative effects on classifier...
In this paper, based on rough set, the design of fuzzy neural network is studied. The character of rough fuzzy neural network and other neural network are analyzed and compared. The validity of the rough fuzzy neural network can be verified in extracting sound quality parameters from the scene image. The rough fuzzy neural network has superiorities at the aspect of structure and convergence.
As the most important objective parameters, reverberation time and clarity play significant roles in acoustic field characteristics evaluation of the hall. We can get it by measuring an actual room. In this paper, a new method is proposed based on adaptive fuzzy neural network to extract the reverberation time and clarity from a scene image. Finally the validity of the network is proved through the...
As the most important objective parameter, reverberation time plays a significant role in acoustic field characteristics evaluation of the hall. We can get it by measuring an actual room. In this paper, a new method is proposed based on rough fuzzy neural network to reckon the reverberation time from a scene image, which is obviously distinguished from the conventional methods. Finally the validity...
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