Wyniki wyszukiwania - BazTech

1

Support vector machine in gender recognition

Stawska Z., Milczarski P.

Information Systems in Management

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2017

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Vol. 6, No. 4

318--329

EN

In the paper, Support Vector Machine (SVM) methods are discussed. The SVM algorithm is a very strong classification tool. Its capability in gender recognition in comparison with the other methods is presented here. Different sets of face features derived from the frontal facial image such as eye corners, nostrils, mouth corners etc. are taken into account. The efficiency of different sets of facial features in gender recognition using SVM method is examined.

2

Gender recogniotion methods useful in mobile authentication applications

Stawska Z., Milczarski P.

Information Systems in Management

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2016

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Vol. 5, No. 2

248--259

EN

Soft biometrics methods that involve gender, age and ethnicity are still developed. Face recognition methods often rely on gender recognition. The same applies to the methods reconstructing the faces or building 2D or 3D models of the faces. In the paper, we conduct study on different set of gender recognition methods and their mobile applications. We show the advantages and disadvantages of that methods and future challenges to the researches. In the previous papers, we examined a range variety of skin detection methods that help to spot the face in the images or video stream. On acquiring faces, we focus on gender recognition that will allow us to create pattern to build 2D and 3D automatic faces models from the images. That will result also in face recognition and authentication, also.

3

Complex colour detection methods used in skin detection systems

Milczarski P., Stawska Z.

Information Systems in Management

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2014

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Vol. 3, No. 1

40--52

EN

In this paper we present high computational complexity algorithms for detecting skin and non-skin colour. Because of their complexity they are not suitable for nowadays mobile devices but can be used in systems working on more demanding machines. The selection and implementation of algorithms gives accuracy about 80-90%.

4

Algorithms and methods used in skin and face detection suitable for mobile applications

Stawska Z., Milczarski P.

Information Systems in Management

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2013

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Vol. 2, No. 3

227--238

EN

Face detection is one of the most important issues in the identification and authentication systems that use biometric features. In this paper we present algorithms for detecting skin colour. The selection and implementation of an algorithm for automated authentication system and face detection can significantly improve the effectiveness of such a system. In the paper we examine several algorithms and methods that can be used in mobile application for authentication purpose i.e. NFC payments.

5

System monitoringu z automatycznym wykrywaniem potencjalnych zagrożeń

Wabik W.

Studia Informatica

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2012

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Vol. 33, nr 2B

497-508

PL

Praca zawiera opis systemu monitoringu budynku. System wyposażony został w moduł sztucznej inteligencji, pozwalający na rozpoznanie widocznych na zdjęciach kamer osób. System umożliwia wykrycie zagrożeń w czasie rzeczywistym oraz analizę zarejestrowanych zdarzeń w celu ich wyjaśnienia.

EN

Publication contains description of building monitoring system. System has AI module to allow it to identify people on camera images. System detects danger situations in real-time and allows user to analyze recorded events.

6

An access control system for e-learning management systems

Irfan A. C.M., Takuya K., Nomura S., Yoshimi F.

Journal of Medical Informatics & Technologies

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2009

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Vol. 13

41--46

EN

Knowledge is a key factor to the personal success. The certifications are the instant tools that are commonly available to assess the personal success. In an e-Learning environment, where the learning projects are delivered with the aim to provide a professional or an academic certification, it is integral that the Learning Management Systems provide security features that will ensure the credibility of the online real-time assessments and the certification. In a conventional examination environment, there will be invigilators to overlook the examinees, on the contrary, in an on-line examination environment; it is vital that an invigilation mechanism is implemented to ensure the integrity of the examination. In this article we present a face based access control system for online e-Learning systems.

7

The method of user's identification using the fusion of wavelet transform and hidden Markov Models

Bobulski J.

Computing, Multimedia and Intelligent Techniques

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2005

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Vol. 1 nr 1

173-179

EN

The work concerns creation of the original FaMar method of user's identification on the basis of the frontal facial image, in which the fusion of Wavelet Transformation (WT) and Hidden Markov Models (HMM) are used for the three parts of face (eyes, nose, mouth); the decision is made on the basis of the sum maximalisation of likelihood of generating of the models observation.

8

Teoretyczne podstawy zastosowań ukrytego modelu Markowa do rozpoznawania wzorców

Fabian P., Szedel J.

Studia Informatica

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2002

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Vol. 23, nr 4

301-328

PL

W ostatnim czasie w dziedzinie rozpoznawania wzorców bardzo rozpowszechniły się metody, w których wykorzystuje się tzw. ukryty model Markowa. Mówiąc najogólniej, ukryty model Markowa jest modelem probabilistycznym wykorzystywanym do analizy przebiegów czasowych o losowym charakterze. W niniejszym opracowaniu zaprezentowano podstawy teoretyczne ukrytego modelu Markowa. Rozważania ograniczono do modeli jednowymiarowych z czasem dyskretnym, z dyskretnymi i ciągłymi obserwacjami. Przedstawiona charakterystyka oprócz podstawowych definicji zawiera również obszerne omówienie zagadnień bezpośrednio związanych z zastosowaniami ukrytego modelu Markowa. W końcowej części pracy zawarto krótki opis przykładowych zastosowań ukrytego modelu Markowa w dziedzinie rozpoznawania wzorców.

EN

Methods that use Hidden Markov Models (HMM) became recently very popular in the domain of pattern recognition. Generally, a HMM is a probabilistic model used in analysis of random sequences. This article presents theoretical bases of HMMs. Only one-dimensional models with discrete time and continuos observation space have been analyzed. Besides of basic definitions, other problems directly related to applications of HMMs have been discussed. The last part of the article presents some examples of pattern recognition problems, which are solved with HMMs.