1,721,051 research outputs found
Theoretical and Experimental Analysis of a Two-Stage System for Classification
No full textWe consider a popular approach to multicategory classification tasks: a two-stage system based on a first (global) classifier with rejection followed by a (local) nearest-neighbor classifier. Patterns which are not rejected by the first classifier are classified according to its output. Rejected patterns are passed to the nearest-neighbor classifier together with the top-it ranking classes returned by the first classifier. The nearest-neighbor classifier, looking at patterns in the top-h classes, classifies the rejected pattern. An editing strategy for the nearest-neighbor reference database, controlled by the first classifier, is also considered. We analyze this system, showing that even if the first level and nearest-neighbor classifiers are not optimal in a Bayes sense, the system as a whole may be optimal. Moreover, we formally relate the response time of the system to the rejection rate of the first classifier and to the other system parameters. The error-response time trade-off is also discussed. Finally, we experimentally study two instances of the system applied to the recognition of handwritten digits. In one system, the first classifier is a fuzzy basis functions network, while in the second system it is a feed-forward neural network. Classification results as well as response times for different settings of the system parameters are reported for both systems
Automatic Approaches for CE-MRI Examination of the Breast: A Survey
No full textBreast cancer is the most frequently diagnosed non-skin cancer in women, the second leading cause of death among women. Early detection of a breast cancer is fundamental for ensuring high survival rate. Imaging techniques are used to identify suspicious modifications of breast tissue. Among these, contrast-enhanced magnetic resonance imaging (CE-MRI) is particularly interesting for its lack of exposure to radiation and its ability to highlight differences in vascularisation, typical of cancer lesions. Automatic or semi-automatic methods are especially useful with this technique, due to the high quantity of data, in the form of 4D images (3D space + time), to be analysed in each test. This survey describes approaches to fully automatic computer-aided detection/diagnosis of breast lesions with CE-MRI, with particular emphasis on computational intelligence techniques
Soft Clustering: Why and How-To
No full textDespite the huge success of machine learning methods in the last decade, a crucial issue is to control the support of the data used in inference, so that data that are too far from the training set are given low confidence by default. The most important class that features this ability is that of prototype-based methods which are based on clustering or vector quantization as a representation learning model. This paper surveys a family of popular soft clustering methods, framing them in a unified formalism. It also discusses the peculiarities of each of them. A large fraction of the paper is devoted to clarifying the role of model parameters and to providing some guidelines on how to set up these parameters
Anomalous sound event detection: A survey of machine learning based methods and applications
No full textWith the development of multi-modal man-machine interaction, audio signal analysis is gaining importance in a field traditionally dominated by video. In particular, anomalous sound event detection offers novel options to improve audio-based man-machine interaction, in many useful applications such as surveillance systems, industrial fault detection and especially safety monitoring, either indoor or outdoor. Event detection from audio can fruitfully integrate visual information and can outperform it in some respects, thus representing a complementary perceptual modality. However, it also presents specific issues and challenges. In this paper, a comprehensive survey of anomalous sound event detection is presented, covering various aspects of the topic, ı.e.feature extraction methods, datasets, evaluation metrics, methods, applications, and some open challenges and improvement ideas that have been recently raised in the literature
The Challenges of Big Data and the Contribution of Fuzzy Logic
No full textIn recent decades we have witnessed a growing investment by all economic sectors in the acquisition of volumes of data characterized not only by ever larger cardinality, but also by increasing number of characteristics for each observed instance [1], and this led to the coining of the term Big-Data
Computational Intelligence Methods for Bioinformatics and Biostatistics
No full text6th International Meeting, CIBB 2009, Genoa, Italy, October 15-17, 2009, Revised Selected Papers
Series: Lecture Notes in Computer Science, Vol. 6160
Subseries: Lecture Notes in Bioinformatics
This book constitutes the thoroughly refereed post-conference proceedings of the Sixth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2009, held in Genova, Italy, in October 2009. The revised 23 full papers presented were carefully reviewed and selected from 57 submissions. The main goal of the CIBB meetings is to provide a forum open to researchers from different disciplines to present and discuss problems concerning computational techniques in tools for bioinformatics, gene expression analysis and new perspectives in bioinformatics together with 4 special sessions on using game-theoretical tools in bioinformatics, combining Bayesian and machine learning approaches in bioinformatics: state of the art and future perspectives, data clustering and bioinformatics (DCB 2009) and on intelligent systems for medical decisions support (ISMDS 2009).
Content Level » Research
Keywords » bioinformatics - ecolutionary information - game theory - gene characterization - gene expression - genetic algorithms - microarray data - mouse brain - neural networks - regulatory gene networks
Related subjects » Artificial Intelligence - Database Management & Information Retrieval - Image Processing - Theoretical Computer Scienc
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