Matches in SemOpenAlex for { <https://semopenalex.org/work/W2019915298> ?p ?o ?g. }
Showing items 1 to 70 of
70
with 100 items per page.
- W2019915298 abstract "The problem of the automatic detection and identification of military vehicles in hyperspectral imagery has many possible solutions. The availability and utility of library spectra and the ability to atmospherically correct image data has great influence on the choice of approach. This paper concentrates on providing a robust solution in the event that library spectra are unavailable or unreliable due to differing atmospheric conditions between the data and reference. The development of a number of techniques for the detection and identification of unknown objects in a scene has continued apace over the past few years. A number of these techniques have been integrated into a Full System Model (FSM) to provide an automatic and robust system drawing upon the advantages of each. The FSM makes use of novel anomaly detectors and spatial processing to extract objects of interest in the scene which are then identified by a pre-trained classifier, typically a multi-class support vector machine. From this point onwards adaptive feedback is used to control the processing of the system. Stages of the processing chain may be augmented by spectral matching and linear unmixing algorithms in an effort to achieve optimum results depending upon the type of data. The Full System Model is described and the boost in performance over each individual stage is demonstrated and discussed." @default.
- W2019915298 created "2016-06-24" @default.
- W2019915298 creator A5014970149 @default.
- W2019915298 creator A5033454522 @default.
- W2019915298 creator A5035885317 @default.
- W2019915298 creator A5043742948 @default.
- W2019915298 creator A5075389736 @default.
- W2019915298 date "2003-09-24" @default.
- W2019915298 modified "2023-09-23" @default.
- W2019915298 title "Full system modeling for hyperspectral target detection and identification" @default.
- W2019915298 doi "https://doi.org/10.1117/12.487052" @default.
- W2019915298 hasPublicationYear "2003" @default.
- W2019915298 type Work @default.
- W2019915298 sameAs 2019915298 @default.
- W2019915298 citedByCount "0" @default.
- W2019915298 crossrefType "proceedings-article" @default.
- W2019915298 hasAuthorship W2019915298A5014970149 @default.
- W2019915298 hasAuthorship W2019915298A5033454522 @default.
- W2019915298 hasAuthorship W2019915298A5035885317 @default.
- W2019915298 hasAuthorship W2019915298A5043742948 @default.
- W2019915298 hasAuthorship W2019915298A5075389736 @default.
- W2019915298 hasConcept C111919701 @default.
- W2019915298 hasConcept C116834253 @default.
- W2019915298 hasConcept C12267149 @default.
- W2019915298 hasConcept C124101348 @default.
- W2019915298 hasConcept C138827492 @default.
- W2019915298 hasConcept C153180895 @default.
- W2019915298 hasConcept C154945302 @default.
- W2019915298 hasConcept C159078339 @default.
- W2019915298 hasConcept C31972630 @default.
- W2019915298 hasConcept C41008148 @default.
- W2019915298 hasConcept C59822182 @default.
- W2019915298 hasConcept C739882 @default.
- W2019915298 hasConcept C76155785 @default.
- W2019915298 hasConcept C86803240 @default.
- W2019915298 hasConcept C94915269 @default.
- W2019915298 hasConcept C95623464 @default.
- W2019915298 hasConceptScore W2019915298C111919701 @default.
- W2019915298 hasConceptScore W2019915298C116834253 @default.
- W2019915298 hasConceptScore W2019915298C12267149 @default.
- W2019915298 hasConceptScore W2019915298C124101348 @default.
- W2019915298 hasConceptScore W2019915298C138827492 @default.
- W2019915298 hasConceptScore W2019915298C153180895 @default.
- W2019915298 hasConceptScore W2019915298C154945302 @default.
- W2019915298 hasConceptScore W2019915298C159078339 @default.
- W2019915298 hasConceptScore W2019915298C31972630 @default.
- W2019915298 hasConceptScore W2019915298C41008148 @default.
- W2019915298 hasConceptScore W2019915298C59822182 @default.
- W2019915298 hasConceptScore W2019915298C739882 @default.
- W2019915298 hasConceptScore W2019915298C76155785 @default.
- W2019915298 hasConceptScore W2019915298C86803240 @default.
- W2019915298 hasConceptScore W2019915298C94915269 @default.
- W2019915298 hasConceptScore W2019915298C95623464 @default.
- W2019915298 hasLocation W20199152981 @default.
- W2019915298 hasOpenAccess W2019915298 @default.
- W2019915298 hasPrimaryLocation W20199152981 @default.
- W2019915298 hasRelatedWork W2041636156 @default.
- W2019915298 hasRelatedWork W2049245941 @default.
- W2019915298 hasRelatedWork W2051197289 @default.
- W2019915298 hasRelatedWork W2116325143 @default.
- W2019915298 hasRelatedWork W2160451891 @default.
- W2019915298 hasRelatedWork W2767080308 @default.
- W2019915298 hasRelatedWork W2783789044 @default.
- W2019915298 hasRelatedWork W2949112254 @default.
- W2019915298 hasRelatedWork W4242764575 @default.
- W2019915298 hasRelatedWork W4291701050 @default.
- W2019915298 isParatext "false" @default.
- W2019915298 isRetracted "false" @default.
- W2019915298 magId "2019915298" @default.
- W2019915298 workType "article" @default.