Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fusão de métodos baseados em minúcias e em cristas para reconhecimento de impressões digitais

Pós-graduação em Ciência da Computação - IBILCE

Análise de desempenho do Criptossistema Fuzzy Vault em aplicações reais

Pós-graduação em Ciência da Computação - IBILCE

Reconhecimento semi-automático de sinus frontais para identificação humana forense baseado na transformada imagem-floresta e no contexto da forma

Pós-graduação em Ciência da Computação - IBILCE

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

Pattern recognition issues on anisotropic smoothed particle hydrodynamics

This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.

Recognition of two morpho-types in eastern South American brackens (Pteridium-Dennstaedtiaceae-Polypodiopsida)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Deep learning architecture for gesture recognition

Pós-graduação em Engenharia Mecânica - FEG

Scanning Electron Microscopy of Male Terminalia and Its Application to Species Recognition and Phylogenetic Reconstruction in the Drosophila saltans Group

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Heterorhabditis amazonensis RSC5 (Rhabditida: Heterorhabditidae) movement and host recognition

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A brief look at the least-squares approach as a classifier applied to restricted-vocabulary speech recognition

In this letter, a speech recognition algorithm based on the least-squares method is presented. Particularly, the intention is to exemplify how such a traditional numerical technique can be applied to solve a signal processing problem that is usually treated by using more elaborated formulations.

Método para reconhecimento de íris baseado na sua região interna

Recognition of individuals through the characteristics of the iris has in recent years become a well accepted technique due to both the high reliability of this procedure and the its non invasiveness. The methods used in such procedures seek information all over the iris, which depending on the algorithm used may result in high computational costs. Considering that most characteristics of the iris are in its inner region the goal of this work is to develop an algorithm for the recognition of individuals using only this region. To bring the outcome of our approach to the level of the best techniques described in the literature this technique has to be further elaborated, even so the results show a promising technique.

Iris Murdoch e Simone de Beauvoir: uma leitura feminista de A fairly honourable defeat e La femme rompue

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The Cuticular Hydrocarbons Profiles in the Colonial Recognition of the Neotropical Eusocial Wasp, Mischocyttarus cassununga (Hymenoptera: Vespidae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Color stability of the artificial iris button in an ocular prosthesis before and after acrylic resin polymerization

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)