Search results for "k-NN"

showing 3 items of 3 documents

HEp-2 Cell Classification with heterogeneous classes-processes based on K-Nearest Neighbours

2014

We present a scheme for the feature extraction and classification of the fluorescence staining patterns of HEp-2 cells in IIF images. We propose a set of complementary processes specific to each class of patterns to search. Our set of processes consists of preprocessing,features extraction and classification. The choice of methods, features and parameters was performed automatically, using the Mean Class Accuracy (MCA) as a figure of merit. We extract a large number (108) of features able to fully characterize the staining pattern of HEp-2 cells. We propose a classification approach based on two steps: the first step follows the one-against-all(OAA) scheme, while the second step follows the…

IIF images K–Nearest-Neighbors (K-NN) multi-class classification one-against-all classification leave-one-out cross validation.Settore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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A Spatial Pyramidal Decomposition Method for ear representation using local dual cross patterns

2019

International audience; In recent years, several scientific works are oriented to develop optimal ear representation, for ear recognition, which is discriminant, compact, and easyto-implement to ensure the best performance in terms of accuracy, computation cost, and storage requirement. In this manner, this paper presents a novel ear representation based on texture analysis framework, which relies mainly on Dual Cross Pattern (DCP) descriptor and Spatial Pyramid Histogram (SPH) method. The features are extracted using DCP descriptor to capture the textural structure then, the SPH of horizontal ear decomposition is applied to obtain the local information. The feature vector representations o…

WLDA[SPI] Engineering Sciences [physics]SPHComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONRECOGNITIOND-LDCPGeneralLiterature_MISCELLANEOUSEar recognition[SPI]Engineering Sciences [physics]ComputingMethodologies_PATTERNRECOGNITIONlcsh:Electrical engineering. Electronics. Nuclear engineeringLDCPlcsh:TK1-9971K-NN
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Regressiomenetelmiä viljapellon biomassan estimointiin ortokuvista ja digitaalisesta korkeusmallista

2012

Tutkielmassa esitellään käyttötarkoitus biomassan estimoinnille ja vertaillaan kolmea regressiomenetelmää, lineaarista regressiota, k:n lähimmän naapurin menetelmää sekä tukivektoriregressiota. Tutkielmassa esitellään myös aineisto ja aineistoon suoritetut muunnokset.

biomassatukivektoriregressiolineaarinen regressiok-NNkonenäköestimointimenetelmät
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