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EN
This paper researches various modelling approaches for website-related predictions, offering an overview of the field. With the ever-expanding landscape of the World Wide Web, there is an increasing need for automated methods to categorize websites. This study examines an array of prediction tasks, including website categorization, web navigation prediction, malicious website detection, fake news website detection, phishing website detection, and evaluation of website aesthetics.
PL
Ten artykuł naukowy przeprowadza analizę różnorodnych metod modelowania stosowanych do prognozowania aspektów witryn internetowych, zapewniając przegląd tej dynamicznie rozwijającej się dziedziny. Podczas gdy Internet nieustannie się powiększa, nabiera wagi potrzeba stosowania automatycznych metod do klasyfikacji nowo powstających stron internetowych. Zbadano metody zastosowane w szerokim zakresie przewidywań, obejmujących kategoryzację witryn internetowych, prognozowanie zachowań nawigacyjnych użytkowników online, identyfikację stron o złośliwym charakterze, wykrywanie fałszywych informacji, rozpoznawanie prób phishingu oraz ocenę estetycznych aspektów witryn internetowych.
EN
LiDAR technology has been widely adopted as a proper method for land cover classification. Recently with the development of technology, LiDAR systems can now capture high-resolution multispectral bands images with high-density LiDAR point cloud simultaneously. Therefore, it opens new opportunities for more precise automatic land-use classification methods by utilizing LiDAR data. This article introduces a combining technique of point cloud classification algorithms. The algorithms include ground detection, building detection, and close point classification - the classification is based on point clouds’ attributes. The main attributes are heigh, intensity, and NDVI index calculated from 4 bands of colors extracted from multispectral images for each point. Data of the Leica City Mapper LiDAR system in an area of 80 ha in Quang Xuong town, Thanh Hoa province, Vietnam was used to deploy the classification. The data is classified into eight different types of land use consist of asphalt road, other ground, low vegetation, medium vegetation, high vegetation, building, water, and other objects. The classification workflow was implemented in the TerraSolid suite, with the result of the automation process came out with 97% overall accuracy of classification points. The classified point cloud is used in a workflow to create a 3D city model LoD2 (Level of Detail) afterward.
EN
Image data from Drones/Unmanned Aerial Vehicles (UAVs) has been studied and used extensively for establishing maps. The process of UAV data provides three main products including (Digital Surface Model) DSM, Point cloud and Ortho-photos, in which point cloud is a valuable data source in building 3D models and topographic surfaces as well. However, processing point cloud separately to achieve secondary products has not been received much attention from researchers. This study determines parameters to develop a method for classifying point cloud data constructed from UAV images. Consequently, A 3D surface of the ground is built by applying a developed algorithm for the point cloud data for an open-pit mine. The temporal or non-ground objects such as trees, houses, vehicles are automatically subtracted from the point cloud by the algorithms. According to this line, it is possible to calculate and analyze the amount of reserves, the exploited volume to evaluate the efficiency for each mine during operation with the support of UAV integrated camera.
PL
Dane uzyskane z dronów / bezzałogowych statków powietrznych (BSP) zostały zbadane i powszechnie wykorzystane do opracowania map. Przetwarzanie danych z BSP zapewnia trzy główne produkty, a mianowicie: Model numeryczny powierzchni (MNS), chmurę punktów i ortofotomapy, w których chmura punktów jest cennym źródłem danych przy budowaniu modeli 3D i powierzchni topograficznych. Dotychczas, kwestia przetwarzania chmury punktów osobno w celu uzyskania produktów wtórnych nie wzbudziła większego zainteresowania naukowców. W artykule, przedstawiono wyniki badania nad sposobem wyznaczenia parametrów niezbędnych do opracowania metod klasyfikacji danych chmur punktów zbudowanych z obrazów BSP. W efekcie tego procesu, powstaje trójwymiarowa powierzchnia powierzchni poprzez zastosowanie opracowanego algorytmu dla danych chmury punktów w kopalni odkrywkowej. Na tej podstawie, można służyć do pomiarów inwentaryzacyjnych, bieżącej kontroli zgodności postępu eksploatacji górniczej z planem ruchu zakładu górniczego, prowadzenia pomiarów postępu frontu eksploatacji w złożu oraz frontów, obejmujących proces zdejmowania nadkładu oraz wyeksploatowanego złoża.
EN
Today’s human-computer interaction systems have a broad variety of applications in which automatic human emotion recognition is of great interest. Literature contains many different, more or less successful forms of these systems. This work emerged as an attempt to clarify which speech features are the most informative, which classification structure is the most convenient for this type of tasks, and the degree to which the results are influenced by database size, quality and cultural characteristic of a language. The research is presented as the case study on Slavic languages.
EN
Imbalanced data classification is one of the most widespread challenges in contemporary pattern recognition. Varying levels of imbalance may be observed in most real datasets, affecting the performance of classification algorithms. Particularly, high levels of imbalance make serious difficulties, often requiring the use of specially designed methods. In such cases the most important issue is often to properly detect minority examples, but at the same time the performance on the majority class cannot be neglected. In this paper we describe a novel resampling technique focused on proper detection of minority examples in a two-class imbalanced data task. The proposed method combines cleaning the decision border around minority objects with guided synthetic oversampling. Results of the conducted experimental study indicate that the proposed algorithm usually outperforms the conventional oversampling approaches, especially when the detection of minority examples is considered.
EN
Decisions regarding appropriate methods for the heat treatment of bronzes affect the final properties obtained in these materials. This study gives an example of the construction of a knowledge base with application of the rough set theory. Using relevant inference mechanisms, knowledge stored in the rule-based database allows the selection of appropriate heat treatment parameters to achieve the required properties of bronze. The paper presents the methodology and the results of exploratory research. It also discloses the methodology used in the creation of a knowledge base.
PL
Decyzje dotyczące odpowiedniej metody obróbki cieplnej brązów mają wpływ na uzyskanie końcowych własności tych materiałów. W pracy przedstawiono przykład budowy bazy wiedzy z zastosowaniem teorii zbiorów przybliżonych. Wiedza zgromadzona w bazie reguł umożliwia za pomocą mechanizmów wnioskowania dobór odpowiednich parametrów obróbki w celu uzyskania pożądanych własności brązu.
EN
The work proposes a new method for vehicle classification, which allows treating vehicles uniformly at the stage of defining the vehicle classes, as well as during the classification itself and the assessment of its correctness. The sole source of information about a vehicle is its magnetic signature normalised with respect to the amplitude and duration. The proposed method allows defining a large number (even several thousand) of classes comprising vehicles whose magnetic signatures are similar according to the assumed criterion with precisely determined degree of similarity. The decision about the degree of similarity and, consequently, about the number of classes, is taken by a user depending on the classification purpose. An additional advantage of the proposed solution is the automated defining of vehicle classes for the given degree of similarity between signatures determined by a user. Thus the human factor, which plays a significant role in currently used methods, has been removed from the classification process at the stage of defining vehicle classes. The efficiency of the proposed approach to the vehicle classification problem was demonstrated on the basis of a large set of experimental data.
EN
The article describes the problem of selection of heat treatment parameters to obtain the required mechanical properties in heat- treated bronzes. A methodology for the construction of a classification model based on rough set theory is presented. A model of this type allows the construction of inference rules also in the case when our knowledge of the existing phenomena is incomplete, and this is situation commonly encountered when new materials enter the market. In the case of new test materials, such as the grade of bronze described in this article, we still lack full knowledge and the choice of heat treatment parameters is based on a fragmentary knowledge resulting from experimental studies. The measurement results can be useful in building of a model, this model, however, cannot be deterministic, but can only approximate the stochastic nature of phenomena. The use of rough set theory allows for efficient inference also in areas that are not yet fully explored.
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