Interval type-2 fuzzy logic can be applied to perform image processing and patternrecognition. In this work a new type-2 fuzzy logic method is applied for edge detection in images and the results are compared with th...
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We evaluate the utility of the periocular region appearance cues for biometric identification. Even though periocular region is considered to be a highly discriminative part of a face, its utility as an independent mo...
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An analysis of the predictability of subcellular locations is performed by using simple patternrecognition techniques in an attempt to capture the real dimensions of the problem at hand. Results show that there are s...
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ISBN:
(纸本)9781424441242
An analysis of the predictability of subcellular locations is performed by using simple patternrecognition techniques in an attempt to capture the real dimensions of the problem at hand. Results show that there are some particular locations that does not need of high complexity classification models to be predicted with high accuracies, and some partial biological explanations are formulated. All the experiments were carried out over a set of Arabidopsis Thaliana proteins and classes were defined according to the plants GO slim.
This paper addresses the problem of traffic sign recognition in real-time conditions. The algorithm presented in this paper is based on detecting traffic signs in life images and videos using pattern matching of the u...
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Many studies have been done on improving Geometric Moment Invariants proposed by Hu since 1962 for patternrecognition. However, many researchers have found that there are some drawbacks with this geometric moment. He...
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ISBN:
(纸本)9783642130328
Many studies have been done on improving Geometric Moment Invariants proposed by Hu since 1962 for patternrecognition. However, many researchers have found that there are some drawbacks with this geometric moment. Hence, this paper presents an integrated formulation of United Moment and Aspect Moment into Zernike Moment Invariant to seek the invarianceness of the solutions. The proposed method will be validated mathematically and experimentally. The validity invarianceness of the proposed method is measured by conducting the intra-class and inter-class analysis. The results of the proposed method are promising and feasible in identifying the similarity and differences of the images accordingly.
in order to help human expert resolve the problem of diagnosing disease, we analyze the comparability and relativity between patternrecognition and disease diagnosis in terms of the solution means, and propose the th...
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This paper summarises the results of using a patternrecognition approach for classifying the condition of wooden railway sleepers. Railway sleeper inspections are currently done manually;visual inspection being the m...
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The majority of multi-class pattern classification techniques are proposed for learning from balanced datasets. However, in several real-world domains, the datasets have imbalanced data distribution, where some classe...
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Opinion Mining (OM) and Sentiment Analysis problems lay in the conjunction of such fields as Information Retrieval and Computational Linguistics. As the problems are semantic oriented, the solution must be looked for ...
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ISBN:
(纸本)9783642106866
Opinion Mining (OM) and Sentiment Analysis problems lay in the conjunction of such fields as Information Retrieval and Computational Linguistics. As the problems are semantic oriented, the solution must be looked for not in data as such, but in its meaning, considering complex (both internal and external,) domain specific context relations. This paper presents Opinion Mining as a specific definition of structural patternrecognition problem. Neuronal Group Learning, earlier presented as general structural data analysis tool, is specialised to infer annotations from natural language text.
Recent works in ubiquitous computing have addressed analysis of electric power for energy conservation by detailing and studying consumption of electrical appliances. We contribute with an approach to develop techniqu...
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ISBN:
(纸本)9781612081007
Recent works in ubiquitous computing have addressed analysis of electric power for energy conservation by detailing and studying consumption of electrical appliances. We contribute with an approach to develop techniques for fingerprinting and monitoring consumption of electric power in households. The approach builds on previous works and employs three phases: feature extraction of attributes such as real power and current harmonic contents, event detection and patternrecognition. A load library is foreseen that stores appliance characteristics as corpus data for training and recognition. We report early findings achieved using a high definition sensor directly applied to the loads showing promising results but also challenges in event detection (smaller state transitions, challenges in detecting and pairing switch on and off events). These studies are important in order to be able to address opportunities of identifying and monitoring directly at the appliance level or sensing the total load of the network. Future applications include monitoring and detailing of loads in a "balance sheet" and context aware service with advice tips for energy users.
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