Matches in SemOpenAlex for { <https://semopenalex.org/work/W2072374234> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W2072374234 endingPage "4434" @default.
- W2072374234 startingPage "4425" @default.
- W2072374234 abstract "This study presents a useful method for semantic-based imagery retrieval. The experiments are made in two parts. In the first part of the experiments, the newly designed one-dimensional hidden Markov models (HMM) in terms of 'observation-sequence' and 'observation-density' manipulation approaches are proposed so as to evaluate the corresponding performance in imagery retrieval accuracy. For the 'observation-sequence' manipulation method, there are totally four neighborhood systems being evaluated, while two neighborhood systems are tested in the 'observation density' manipulation domain. In the second part of the experiments, a C4.5 decision tree is introduced and trained by the HMM likelihoods so as to discover the retrieving rules to further enhance the imagery retrieval accuracy. The test imagery all belong to real-scene military vehicles and are hierarchically pre-processed using wavelet and LAB transforms. The imagery are classified into 'Air-Force', 'Warship', 'Submarine', 'Tank', and 'Jeep', respectively. It is found that using HMM alone can achieve the best accuracy of 68.8%, when decision trees are implemented, the accuracy can be further enhanced up to 78%. The results evidentially show the usefulness of the method, and can be used in intelligent systems in recognizing real-scene objects." @default.
- W2072374234 created "2016-06-24" @default.
- W2072374234 creator A5006327315 @default.
- W2072374234 creator A5030480573 @default.
- W2072374234 date "2010-06-01" @default.
- W2072374234 modified "2023-09-27" @default.
- W2072374234 title "Multi-resolution semantic-based imagery retrieval using hidden Markov models and decision trees" @default.
- W2072374234 cites W1508960934 @default.
- W2072374234 cites W1523271034 @default.
- W2072374234 cites W1995875735 @default.
- W2072374234 cites W2002268347 @default.
- W2072374234 cites W2007321142 @default.
- W2072374234 cites W2024581784 @default.
- W2072374234 cites W2033341974 @default.
- W2072374234 cites W2039097228 @default.
- W2072374234 cites W2062024414 @default.
- W2072374234 cites W2068874033 @default.
- W2072374234 cites W2073385196 @default.
- W2072374234 cites W2077325236 @default.
- W2072374234 cites W2077574412 @default.
- W2072374234 cites W2082953961 @default.
- W2072374234 cites W2086699924 @default.
- W2072374234 cites W2098166271 @default.
- W2072374234 cites W2110249778 @default.
- W2072374234 cites W2111048828 @default.
- W2072374234 cites W2125838338 @default.
- W2072374234 cites W2137545186 @default.
- W2072374234 cites W2170418652 @default.
- W2072374234 cites W2219873312 @default.
- W2072374234 doi "https://doi.org/10.1016/j.eswa.2009.11.086" @default.
- W2072374234 hasPublicationYear "2010" @default.
- W2072374234 type Work @default.
- W2072374234 sameAs 2072374234 @default.
- W2072374234 citedByCount "4" @default.
- W2072374234 countsByYear W20723742342013 @default.
- W2072374234 countsByYear W20723742342014 @default.
- W2072374234 countsByYear W20723742342016 @default.
- W2072374234 crossrefType "journal-article" @default.
- W2072374234 hasAuthorship W2072374234A5006327315 @default.
- W2072374234 hasAuthorship W2072374234A5030480573 @default.
- W2072374234 hasConcept C153180895 @default.
- W2072374234 hasConcept C154945302 @default.
- W2072374234 hasConcept C204321447 @default.
- W2072374234 hasConcept C23123220 @default.
- W2072374234 hasConcept C23224414 @default.
- W2072374234 hasConcept C41008148 @default.
- W2072374234 hasConcept C84525736 @default.
- W2072374234 hasConceptScore W2072374234C153180895 @default.
- W2072374234 hasConceptScore W2072374234C154945302 @default.
- W2072374234 hasConceptScore W2072374234C204321447 @default.
- W2072374234 hasConceptScore W2072374234C23123220 @default.
- W2072374234 hasConceptScore W2072374234C23224414 @default.
- W2072374234 hasConceptScore W2072374234C41008148 @default.
- W2072374234 hasConceptScore W2072374234C84525736 @default.
- W2072374234 hasIssue "6" @default.
- W2072374234 hasLocation W20723742341 @default.
- W2072374234 hasOpenAccess W2072374234 @default.
- W2072374234 hasPrimaryLocation W20723742341 @default.
- W2072374234 hasRelatedWork W1507687735 @default.
- W2072374234 hasRelatedWork W1548481688 @default.
- W2072374234 hasRelatedWork W2023185280 @default.
- W2072374234 hasRelatedWork W2154383834 @default.
- W2072374234 hasRelatedWork W2167236583 @default.
- W2072374234 hasRelatedWork W2539985974 @default.
- W2072374234 hasRelatedWork W2546624495 @default.
- W2072374234 hasRelatedWork W2963474932 @default.
- W2072374234 hasRelatedWork W3107474891 @default.
- W2072374234 hasRelatedWork W4301681594 @default.
- W2072374234 hasVolume "37" @default.
- W2072374234 isParatext "false" @default.
- W2072374234 isRetracted "false" @default.
- W2072374234 magId "2072374234" @default.
- W2072374234 workType "article" @default.