FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4306293874> ?p ?o ?g. }

• W4306293874 endingPage "1845" @default.
• W4306293874 startingPage "1837" @default.
• W4306293874 abstract "Seeing alcohol in media has been demonstrated to increase alcohol craving, impulsive decision-making, and hazardous drinking. Due to the exponential growth of (social) media use it is important to develop algorithms to quantify alcohol exposure efficiently in electronic images. In this article, we describe the development of an improved version of the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA), called ABIDLA2.ABIDLA2 was trained on 191,286 images downloaded from Google Image Search results (based on search terms) and Bing Image Search results. In Task-1, ABIDLA2 identified images as containing one of eight beverage categories (beer/cider cup, beer/cider bottle, beer/cider can, wine, champagne, cocktails, whiskey/cognac/brandy, other images). In Task-2, ABIDLA2 made a binary classification between images containing an alcoholic beverage or other. An ablation study was performed to determine which techniques improved algorithm performance.ABIDLA2 was most accurate in identifying Whiskey/Cognac/Brandy (88.1%) followed by Beer/Cider Can (80.5%), Beer/Cider Bottle (78.3%), and Wine (77.8%). Its overall accuracy was 77.0% (Task-1) and 87.7% (Task-2). Even the identification of the least accurate beverage category (Champagne, 64.5%) was more than five times higher than random chance (12.5% = 1/8 categories). The implementation of balanced data sampler to address class skewness and the use of self-training to make use of a large, secondary, weakly labeled dataset particularly improved overall algorithm performance.With extended capabilities and a higher accuracy, ABIDLA2 outperforms its predecessor and enables the screening of any kind of electronic media rapidly to estimate the quantity of alcohol exposure. Quantifying alcohol exposure automatically through algorithms like ABIDLA2 is important because viewing images of alcoholic beverages in media tends to increase alcohol consumption and related harms." @default.
• W4306293874 created "2022-10-15" @default.
• W4306293874 creator A5066484953 @default.
• W4306293874 creator A5067911307 @default.
• W4306293874 creator A5072802156 @default.
• W4306293874 creator A5087195057 @default.
• W4306293874 date "2022-10-01" @default.
• W4306293874 modified "2023-09-26" @default.
• W4306293874 title "Development and validation of the Alcoholic Beverage Identification Deep Learning Algorithm version 2 for quantifying alcohol exposure in electronic images" @default.
• W4306293874 cites W1978323880 @default.
• W4306293874 cites W2029227883 @default.
• W4306293874 cites W2096387872 @default.
• W4306293874 cites W2110244245 @default.
• W4306293874 cites W2117539524 @default.
• W4306293874 cites W2143329892 @default.
• W4306293874 cites W2164777277 @default.
• W4306293874 cites W2963446712 @default.
• W4306293874 cites W2971644666 @default.
• W4306293874 cites W2989051262 @default.
• W4306293874 cites W2999380858 @default.
• W4306293874 cites W3009019824 @default.
• W4306293874 cites W3035160371 @default.
• W4306293874 cites W3088745370 @default.
• W4306293874 cites W3107120086 @default.
• W4306293874 cites W4306293874 @default.
• W4306293874 doi "https://doi.org/10.1111/acer.14925" @default.
• W4306293874 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36242596" @default.
• W4306293874 hasPublicationYear "2022" @default.
• W4306293874 type Work @default.
• W4306293874 citedByCount "6" @default.
• W4306293874 countsByYear W43062938742022 @default.
• W4306293874 countsByYear W43062938742023 @default.
• W4306293874 crossrefType "journal-article" @default.
• W4306293874 hasAuthorship W4306293874A5066484953 @default.
• W4306293874 hasAuthorship W4306293874A5067911307 @default.
• W4306293874 hasAuthorship W4306293874A5072802156 @default.
• W4306293874 hasAuthorship W4306293874A5087195057 @default.
• W4306293874 hasBestOaLocation W43062938741 @default.
• W4306293874 hasConcept C116834253 @default.
• W4306293874 hasConcept C119857082 @default.
• W4306293874 hasConcept C127413603 @default.
• W4306293874 hasConcept C153180895 @default.
• W4306293874 hasConcept C154945302 @default.
• W4306293874 hasConcept C185592680 @default.
• W4306293874 hasConcept C201995342 @default.
• W4306293874 hasConcept C2780451532 @default.
• W4306293874 hasConcept C31903555 @default.
• W4306293874 hasConcept C32236832 @default.
• W4306293874 hasConcept C41008148 @default.
• W4306293874 hasConcept C55952523 @default.
• W4306293874 hasConcept C59822182 @default.
• W4306293874 hasConcept C78519656 @default.
• W4306293874 hasConcept C86803240 @default.
• W4306293874 hasConceptScore W4306293874C116834253 @default.
• W4306293874 hasConceptScore W4306293874C119857082 @default.
• W4306293874 hasConceptScore W4306293874C127413603 @default.
• W4306293874 hasConceptScore W4306293874C153180895 @default.
• W4306293874 hasConceptScore W4306293874C154945302 @default.
• W4306293874 hasConceptScore W4306293874C185592680 @default.
• W4306293874 hasConceptScore W4306293874C201995342 @default.
• W4306293874 hasConceptScore W4306293874C2780451532 @default.
• W4306293874 hasConceptScore W4306293874C31903555 @default.
• W4306293874 hasConceptScore W4306293874C32236832 @default.
• W4306293874 hasConceptScore W4306293874C41008148 @default.
• W4306293874 hasConceptScore W4306293874C55952523 @default.
• W4306293874 hasConceptScore W4306293874C59822182 @default.
• W4306293874 hasConceptScore W4306293874C78519656 @default.
• W4306293874 hasConceptScore W4306293874C86803240 @default.
• W4306293874 hasIssue "10" @default.
• W4306293874 hasLocation W43062938741 @default.
• W4306293874 hasLocation W43062938742 @default.
• W4306293874 hasLocation W43062938743 @default.
• W4306293874 hasOpenAccess W4306293874 @default.
• W4306293874 hasPrimaryLocation W43062938741 @default.
• W4306293874 hasRelatedWork W118488366 @default.
• W4306293874 hasRelatedWork W1975418603 @default.
• W4306293874 hasRelatedWork W2022957626 @default.
• W4306293874 hasRelatedWork W204568091 @default.
• W4306293874 hasRelatedWork W2056206426 @default.
• W4306293874 hasRelatedWork W2102768196 @default.
• W4306293874 hasRelatedWork W2278785198 @default.
• W4306293874 hasRelatedWork W2793174909 @default.
• W4306293874 hasRelatedWork W2997704545 @default.
• W4306293874 hasRelatedWork W4280630119 @default.
• W4306293874 hasVolume "46" @default.
• W4306293874 isParatext "false" @default.
• W4306293874 isRetracted "false" @default.
• W4306293874 workType "article" @default.