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The following topics are dealt with : hidden Markov model; support vector machines; microarray sample classification; automated knowledge engineering; medical image edge enhancement; recurrent fuzzy multilayer perceptron; self organizing maps; data mining; business intelligence tool; context ontology driven relevant search; Web search result optimization; image compression analysis; natural feature...
Soft computing in the area of information security is a promising field for the creation of intelligent solutions. This paper discusses a method for digital watermarking using artificial neural networks to realize secure copyright protection of visual information without any damage. The discussed watermark extraction keys and feature extraction keys identify the secure and unique hidden patterns for...
We focus the attention on the audio scene segmentation in AAC domain for audio-based multimedia indexing and retrieval applications. In particular, a MFCC extraction method is proposed, which is adaptive to the window switch in AAC encoding process, and independent of the audio sampling frequency. We discuss the fusion method of MFCC features, which came from different window type in order to keep...
Automatic text summarization is a wide research area. Automatic text summarization is to compress the original text into a shorter version and help the user to quickly understand large volumes of information. There are several ways in which one can characterize different approaches to text summarization: extractive and abstractive from single document or multi document. This paper focuses on the automatic...
During the last years, a number of search and retrieval methods for audio and visual content were described in literature. Also cross-modal approaches started to emerge recently. All search methods are based on audiovisual fingerprints, which are extracted from the audiovisual data prior to the actual search. Since the most data are available in the compressed domain, they must be decompressed prior...
Dimensionality reduction is a necessary preprocessing step in many fields of information processing such as information retrieval, pattern recognition and data compression. Its goal is to discover the representative or the discriminative information residing in raw data. Locally linear embedding (LLE), one of effective manifold learning algorithms, addresses this problem by computing low-dimensional,...
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