FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3209568560> ?p ?o ?g. }

• W3209568560 endingPage "301311" @default.
• W3209568560 startingPage "301311" @default.
• W3209568560 abstract "Estimating the acquisition time of digital photographs is a challenging task in temporal image forensics, but the application is highly demanded for establishing temporal order among individual pieces of evidence and deduce the causal relationship of events in a court case. The forensic investigator needs to identify the timeline of events and look for some patterns to gain a clear overview of activities associated with a crime. This paper aims to explore the presence of defective pixels over time for estimating the acquisition date of digital pictures. We propose a technique to predict the acquisition timeslots of digital pictures using a set of candidate defective pixels in non-overlapping image blocks. First, potential candidate defective pixels are determined through related pixel neighbourhood and two proposed features, called the local variation features to best fit in a machine learning model. The machine learning approach is used to model the temporal behaviour of camera sensor defects in each block using the scores obtained from individually trained pixel defect locations and fused in a majority voting method. Interestingly, timeslot estimation using individual blocks has been shown to be more accurate when virtual sub-classes corresponding to halved timeslots are first considered prior to the reconstruction step. Finally, the last stage of the system consists of the combination of block scores in a second majority voting operation to further enhance performance. Assessed on the NTIF image dataset, the proposed system has been shown to reach very promising results with an estimated accuracy between 88% and 93% and clear superiority over a related state-of-the-art system. • Acquisition time estimation of digital pictures is a challenging task in temporal image forensics. • Forensic investigators need a correct timeline of suspect images to answer the questions during an investigation. • Using defective pixel locations, the acquisition timeslots of digital pictures can be predicted. • Temporal behavior of defective pixels can be analyzed through machine learning technique." @default.
• W3209568560 created "2021-11-08" @default.
• W3209568560 creator A5006589533 @default.
• W3209568560 creator A5007128912 @default.
• W3209568560 creator A5033623398 @default.
• W3209568560 creator A5041241660 @default.
• W3209568560 date "2021-12-01" @default.
• W3209568560 modified "2023-09-24" @default.
• W3209568560 title "A machine learning-based approach for picture acquisition timeslot prediction using defective pixels" @default.
• W3209568560 cites W2007121330 @default.
• W3209568560 cites W2081849221 @default.
• W3209568560 cites W2328840452 @default.
• W3209568560 cites W2560868627 @default.
• W3209568560 cites W2586028541 @default.
• W3209568560 cites W2639913090 @default.
• W3209568560 cites W2781647282 @default.
• W3209568560 cites W2792052036 @default.
• W3209568560 cites W2886155985 @default.
• W3209568560 cites W2963987269 @default.
• W3209568560 cites W2964089686 @default.
• W3209568560 cites W2976510523 @default.
• W3209568560 cites W3142913228 @default.
• W3209568560 cites W3157130709 @default.
• W3209568560 doi "https://doi.org/10.1016/j.fsidi.2021.301311" @default.
• W3209568560 hasPublicationYear "2021" @default.
• W3209568560 type Work @default.
• W3209568560 sameAs 3209568560 @default.
• W3209568560 citedByCount "2" @default.
• W3209568560 countsByYear W32095685602023 @default.
• W3209568560 crossrefType "journal-article" @default.
• W3209568560 hasAuthorship W3209568560A5006589533 @default.
• W3209568560 hasAuthorship W3209568560A5007128912 @default.
• W3209568560 hasAuthorship W3209568560A5033623398 @default.
• W3209568560 hasAuthorship W3209568560A5041241660 @default.
• W3209568560 hasConcept C105795698 @default.
• W3209568560 hasConcept C119857082 @default.
• W3209568560 hasConcept C153180895 @default.
• W3209568560 hasConcept C154945302 @default.
• W3209568560 hasConcept C160633673 @default.
• W3209568560 hasConcept C177264268 @default.
• W3209568560 hasConcept C199360897 @default.
• W3209568560 hasConcept C2524010 @default.
• W3209568560 hasConcept C2777210771 @default.
• W3209568560 hasConcept C31972630 @default.
• W3209568560 hasConcept C33923547 @default.
• W3209568560 hasConcept C41008148 @default.
• W3209568560 hasConcept C4438859 @default.
• W3209568560 hasConceptScore W3209568560C105795698 @default.
• W3209568560 hasConceptScore W3209568560C119857082 @default.
• W3209568560 hasConceptScore W3209568560C153180895 @default.
• W3209568560 hasConceptScore W3209568560C154945302 @default.
• W3209568560 hasConceptScore W3209568560C160633673 @default.
• W3209568560 hasConceptScore W3209568560C177264268 @default.
• W3209568560 hasConceptScore W3209568560C199360897 @default.
• W3209568560 hasConceptScore W3209568560C2524010 @default.
• W3209568560 hasConceptScore W3209568560C2777210771 @default.
• W3209568560 hasConceptScore W3209568560C31972630 @default.
• W3209568560 hasConceptScore W3209568560C33923547 @default.
• W3209568560 hasConceptScore W3209568560C41008148 @default.
• W3209568560 hasConceptScore W3209568560C4438859 @default.
• W3209568560 hasFunder F4320309815 @default.
• W3209568560 hasFunder F4320332753 @default.
• W3209568560 hasLocation W32095685601 @default.
• W3209568560 hasOpenAccess W3209568560 @default.
• W3209568560 hasPrimaryLocation W32095685601 @default.
• W3209568560 hasRelatedWork W121273120 @default.
• W3209568560 hasRelatedWork W2002009170 @default.
• W3209568560 hasRelatedWork W2034462085 @default.
• W3209568560 hasRelatedWork W2090093270 @default.
• W3209568560 hasRelatedWork W2337415362 @default.
• W3209568560 hasRelatedWork W2546871836 @default.
• W3209568560 hasRelatedWork W2740820121 @default.
• W3209568560 hasRelatedWork W3005455252 @default.
• W3209568560 hasRelatedWork W317572212 @default.
• W3209568560 hasRelatedWork W4312857205 @default.
• W3209568560 hasVolume "39" @default.
• W3209568560 isParatext "false" @default.
• W3209568560 isRetracted "false" @default.
• W3209568560 magId "3209568560" @default.
• W3209568560 workType "article" @default.