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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F06%3A00041079%21RIV07-AV0-67985556
rdf:type
skos:Concept n12:Vysledek
dcterms:description
Návrh klasifikátoru dopravních značek založeného na podobnosti zkoumaného objektu ke třídě značek reprezentované vždy typickou značkou (prototype-based rule). Navržen algoritmus založený na trénování podle množiny prototypů (trainable similarity). Experimenty na několika datových souborech ilustrují vyšší účinnost klasifikátoru v porovnání s klasifikátory až dosud používanými pro klasifikaci značek. Byly testovány i další vlastnosti navrženého klasifikátoru jako robustnost a časová náročnost. A frequently used strategy for road sign classification is based on the normalized cross-correlation similarity to class prototypes followed by the nearest neighbor classifier. Because of the global nature of the cross-correlation similarity, this method suffers from presence of uninformative pixels (caused e.g. by occlusions), and is computationally demanding. In this paper, a novel concept of a trainable similarity measure is introduced which alleviates these shortcomings. The similarity is based on individual matches in a set of local image regions. The set of regions, relevant for a particular similarity assessment, is refined by the training process. It is illustrated on a set of experiments with road sign classification problems that the trainable similarity yields high-performance data representations and classifiers. Apart from a multi-class classification accuracy, also non-sign rejection capability, and computational demands in execution are discussed. It appears that the trainable simi... A frequently used strategy for road sign classification is based on the normalized cross-correlation similarity to class prototypes followed by the nearest neighbor classifier. Because of the global nature of the cross-correlation similarity, this method suffers from presence of uninformative pixels (caused e.g. by occlusions), and is computationally demanding. In this paper, a novel concept of a trainable similarity measure is introduced which alleviates these shortcomings. The similarity is based on individual matches in a set of local image regions. The set of regions, relevant for a particular similarity assessment, is refined by the training process. It is illustrated on a set of experiments with road sign classification problems that the trainable similarity yields high-performance data representations and classifiers. Apart from a multi-class classification accuracy, also non-sign rejection capability, and computational demands in execution are discussed. It appears that the trainable simi...
dcterms:title
Klasifikace dopravních značek založená na míře podobnosti zkoumaného objektu k třídě reprezentované typickou značkou Building Road-Sign Classifiers Using a Trainable Similarity Measure Building Road-Sign Classifiers Using a Trainable Similarity Measure
skos:prefLabel
Building Road-Sign Classifiers Using a Trainable Similarity Measure Klasifikace dopravních značek založená na míře podobnosti zkoumaného objektu k třídě reprezentované typickou značkou Building Road-Sign Classifiers Using a Trainable Similarity Measure
skos:notation
RIV/67985556:_____/06:00041079!RIV07-AV0-67985556
n3:strany
309;321
n3:aktivita
n4:P n4:Z n4:R
n3:aktivity
P(2C06019), P(IAA2075302), R, Z(AV0Z10750506)
n3:cisloPeriodika
3
n3:dodaniDat
n11:2007
n3:domaciTvurceVysledku
n16:6956432
n3:druhVysledku
n17:J
n3:duvernostUdaju
n7:S
n3:entitaPredkladatele
n13:predkladatel
n3:idSjednocenehoVysledku
467503
n3:idVysledku
RIV/67985556:_____/06:00041079
n3:jazykVysledku
n15:eng
n3:klicovaSlova
classifier system design; road-sign classification; similarity data representation
n3:klicoveSlovo
n8:road-sign%20classification n8:classifier%20system%20design n8:similarity%20data%20representation
n3:kodStatuVydavatele
US - Spojené státy americké
n3:kontrolniKodProRIV
[3DEDEC319B33]
n3:nazevZdroje
IEEE Transactions on Intelligent Transportation Systems
n3:obor
n14:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
3
n3:projekt
n10:IAA2075302 n10:2C06019
n3:rokUplatneniVysledku
n11:2006
n3:svazekPeriodika
7
n3:tvurceVysledku
Paclík, P. Novovičová, Jana Duin, R. P. W.
n3:zamer
n18:AV0Z10750506
s:issn
1524-9050
s:numberOfPages
13