Stock assessment and fishery management of the pink shrimp Farfantepenaeus brasiliensis Latreille, 1970 and F. paulensis Pérez-Farfante, 1967 in Southeastern Brazil (23° to 28° S)

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

A Lagrangian relaxation approach to a coupled lot-sizing and cutting stock problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.