Search results for "computer.software_genre"
showing 10 items of 3858 documents
HUMAN BEHAVIOR IN A MULTI-CRITERIA CHOICE PROBLEM WITH INDIVIDUAL TASKS OF DIFFERENT DIFFICULTIES
2003
This paper is devoted to a laboratory study of human behavior in a multi-criteria choice problem. The specific feature of the experimental study is the creation of an individually adjusted instance of a general task for each subject in accordance with his/her preferences over each criterion. Human behavior is studied in a specially constructed choice situation based on the decomposition of the alternatives of a multi-criteria problem. The procedure is based on multiple steps of pair-wise comparisons involving only some (two or three) of the original components of the alternatives. Abilities of subjects to use such comparisons and to answer the questions in a logical way are tested. The exp…
MedAI: Transparency in Medical Image Segmentation
2021
MedAI: Transparency in Medical Image Segmentation is a challenge held for the first time at the Nordic AI Meet that focuses on medical image segmentation and transparency in machine learning (ML)-based systems. We propose three tasks to meet specific gastrointestinal image segmentation challenges collected from experts within the field, including two separate segmentation scenarios and one scenario on transparent ML systems. The latter emphasizes the need for explainable and interpretable ML algorithms. We provide a development dataset for the participants to train their ML models, tested on a concealed test dataset.
Advances in the statistical methodology for the selection of image descriptors for visual pattern representation and classification
1995
Recent advances in the statistical methodology for selecting optimal subsets of features (image descriptors) for visual pattern representation and classification are presented. The paper attempts to provide a guideline about which approach to choose with respect to the a priori knowledge of the problem. Two basic approaches are reviewed and the conditions under which they should be used are specified. References to more detailed material about each one of the methods are given and experimental results supporting the main conclusions are briefly outlined.
Interoperability of Information Systems
2005
An information system is a multilevel system characterized by a “data” level, a “behavioral” level, and a “communication” level. The data level represents the data stored by the system. The behavioral level represents management and production processes carried out by the system. The processes can interact with the data level to extract, generate, and store data. The communication level relates to the network used to exchange data and activate processes between geographically distant users or machines.
Adding Synthetic Detail to Natural Terrain Using a Wavelet Approach
2002
Terrain representation is a basic topic in the field of interactive graphics. The amount of data required for good quality terrain representation offers an important challenge to developers of such systems. For users of these applications the accuracy of geographical data is less important than their natural visual appearance. This makes it possible to mantain a limited geographical data base for the system and to extend it generating synthetic data.In this paper we combine fractal and wavelet theories to provide extra data which keeps the natural essence of actual information available. The new levels of detail(LOD) for the terrain are obtained applying an inverse Wavelet Transform (WT) to…
<title>Dynamic integration of multiple data mining techniques in a knowledge discovery management system</title>
1999
One of the most important directions in improvement of data mining and knowledge discovery, is the integration of multiple classification techniques of an ensemble of classifiers. An integration technique should be able to estimate and select the most appropriate component classifiers from the ensemble. We present two variations of an advanced dynamic integration technique with two distance metrics. The technique is one variation of the stacked generalization method, with an assumption that each of the component classifiers is the best one, inside a certain sub area of the entire domain area. Our technique includes two phases: the learning phase and the application phase. During the learnin…
Multivariate statistical technique over QoS variables to analyze video quality metrics on IEEE 802.11ac networks
2017
[EN] We present the results from a measurementbasedperformance evaluation of wireless networks basedon IEEE 802.11ac standard in an indoor environment, withthe aim to analyze their performance under high definitionstreaming video applications. We focus our study on analyzingthe highest performance of these standards using off-theshelfequipment as well as the behavior of Quality of Servicevariables and how they affect to the video quality. Thus, wehave analyzed and measured these variables and have applieda multivariate statistical technique, called Factor Analysis,and finally discuss their behavior.
Application of the Error Correcting Grammatical Inference Method (ECGI) to Multi-Speaker Isolated Word Recognition
1988
It is well known that speech signals constitute highly structured objects which are composed of different kinds of subobjects such as words, phonemes, etc. This fact has motivated several researchers to propose different models which more or less explicitly assume the structural nature of speech. Notable examples of these models are Markov models /Bak 75/, /Jel 76/; the famous Harpy /Low 76/; Scriber and Lafs /Kla 80/; and many others works in which the convenience of some structural model of the speech objects considered is explicitly claimed /Gup 82/, /Lev 83/, /Cra 84/, /Sca 85/, /Kam 85/, /Sau 85/, /Rab 85/, /Kop 85/, /Sch 85/, /Der 86/, /Tan 86/.
A practical solution to the problem of automatic word sense induction
2004
Recent studies in word sense induction are based on clustering global co-occurrence vectors, i.e. vectors that reflect the overall behavior of a word in a corpus. If a word is semantically ambiguous, this means that these vectors are mixtures of all its senses. Inducing a word's senses therefore involves the difficult problem of recovering the sense vectors from the mixtures. In this paper we argue that the demixing problem can be avoided since the contextual behavior of the senses is directly observable in the form of the local contexts of a word. From human disambiguation performance we know that the context of a word is usually sufficient to determine its sense. Based on this observation…
Machine Learning Techniques for Automatic Depression Assessment
2018
Depression is one of the most common mood disorder that is inherently related to emotions, involving bad mood, low self-esteem and loss of interest in normal pleasurable activities. The aim of this work is to develop a framework based on the dataset provided by AVEC'14 for depression assessment. The proposed work presents two different motion representation methods: a) Gabor Motion History Image (GMHI), and b) Motion History Image (MHI). Several combinations of appearance-based low level features are extracted from both motion representations. These features were further combined with statistically derived features, and used for training and testing with several machine learning techniques.…