Mutual information (MI) is a powerful concept for correlation-centric applications. Recently, it has been used for feature selection for microarray gene expression data. One of the merits of MI is, unlike many other h...
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Two of the most significant factors in the success of today's system-on-chip (SoC) designs are the ability to deliver efficient access to off-chip high speed memory and the ability to be compatible with several di...
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This paper proposes new text summarization approaches based on textual unit association networks. Textual units refer to words, phrases, sentences, or paragraphs. Intuitively, textual units containing much co-occurren...
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In the paper, a new parallel LZW-Like algorithm, bidirectory LZW algorithm (BD-LZW) will be interpreted The new algorithm can be used in data compression/decompression system which runs on multi-microprocessor system,...
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We propose a cascaded linear model for joint Chinese word segmentation and partof- speech tagging. With a character-based perceptron as the core, combined with realvalued features such as language models, the cascaded...
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Among syntax-based translation models, the tree-based approach, which takes as input a parse tree of the source sentence, is a promising direction being faster and simpler than its string-based counterpart. However, c...
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This paper presents an experimental study of environment recognition and movement control of an autonomous two-wheeled mobile robot using infrared range finding sensors. PSD sensors are arranged to detect obstacles an...
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This paper presents an experimental study of environment recognition and movement control of an autonomous two-wheeled mobile robot using infrared range finding sensors. PSD sensors are arranged to detect obstacles and walls in the surroundings of the robot, and environment features are estimated using a set of range sensors data. The experimental mobile robot uses incremental encoders mounted on the wheels to locate itself in a small area. Using these sensors, some intelligent behaviors, such as wall following and obstacle rounding, have been implemented. Upon these behavior modules, the behavior control system is constructed for sensory navigation without any environment map and global selflocalization. The experimental results show that the mobile robot can carry out a navigation task, even when the robot knows little about the environment.
This paper presents an experimental study of distributed cooperative formation control of a team of autonomous mobile robots. Formation control demands that a team of robots keep a specified pattern while moving in a ...
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This paper presents an experimental study of distributed cooperative formation control of a team of autonomous mobile robots. Formation control demands that a team of robots keep a specified pattern while moving in a cluttered environment. So reactive control behaviors for keeping formation and obstacle avoidance are described. The behavioral decision to direct the movement of robot is made by the arbitration of primitive behaviors. For a team of two robots, control experiments were conducted using small mobile robots with infrared photo transistors and LEDs mounted on the front and back of the robot body, respectively. Simulations and real experiments using two mobile robots were successfully performed.
A novel algorithm for image super-resolution with class-specific predictors is proposed in this paper. In our algorithm, the training example images are classified into several classes, and each patch of a low-resolut...
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ISBN:
(纸本)9781424423101
A novel algorithm for image super-resolution with class-specific predictors is proposed in this paper. In our algorithm, the training example images are classified into several classes, and each patch of a low-resolution image is classified into one of these classes. Each class has its high-frequency information inferred using a class-specific predictor, which is trained via the training samples from the same class. In this paper, two different types of training sets are employed to investigate the impact of the training database to be used. Experimental results have shown the superior performance of our method.
Word Sense Disambiguation (WSD) is a process of identifying proper meaning of words that may have multiple meanings. It is regarded as one of the most challenging problems in the field of Natural Language processing (...
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Word Sense Disambiguation (WSD) is a process of identifying proper meaning of words that may have multiple meanings. It is regarded as one of the most challenging problems in the field of Natural Language processing (NLP). Nepali Language also has words that have multiple meanings, thus giving rise to the problem of WSD in it. In this paper, we investigate the impact of NLP resources like Morphology Analyzer (MA) and Machine Readable Dictionary (MRD) in ambiguity resolution. Our results show that the accuracy in WSD is better with the availability of NLP resources like Morph Analyzer, MRD etc. Lesk algorithm has been used to solve WSD problem using a sample Nepali WordNet containing few sets of Nepali nouns and the system is able to disambiguate these nouns only. The system was tested on a small set of data with limited number of nouns. The accuracy reading was between 50%-70% depending on the sample data provided. When the same data was tested through manual morph analysis, the accuracy was seen to be considerably high (80%).
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