FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4375952661> ?p ?o ?g. }

• W4375952661 endingPage "107877" @default.
• W4375952661 startingPage "107877" @default.
• W4375952661 abstract "Analysis of piglet suckling behaviour is important for the evaluation of piglet nutrient ingestion, health, welfare, and affinity with the sow. In this study, an action density estimation network (ADEN) was proposed for counting the events of piglet suckling followed by automated analysis of suckling behaviour. ADEN is a two-stream network primarily composed of 1) a network stream that processes video images with a higher frame rate (faster stream) and 2) a network stream that processes video images with a lower frame rate (slower stream). Each stream consists of a ResNet-50 with five convolutional stages. A multi-stage attention connection (MSAC), composed of four Spatial-Temporal-Channel (STC) multi-attention structures, is proposed to bridge Faster Stream and Slower Stream and capture discriminative features. The output attention features from each faster stream stage are laterally fused into the corresponding slower stream stage in a concatenating manner. Following this, the features from the last convolutional stages in the Slow stream and Fast stream are fused using concatenation and are then decoded by using three convolutional layers. The last convolutional layer outputs a heatmap on the action density of piglet suckling behaviour. Finally, the number of suckling events is predicted by integrating all the pixel values in the heatmap. Experimental and comparative tests were conducted to validate the effectiveness of the proposed ADEN with a training dataset and a test dataset from 14 pig pens. The 507 video clips (126,750 images for 7 h) from the 1-9th pens were selected as training datasets. The 143 video clips (35,750 images for 2 h) from the 10-13th pens were selected as short-term test datasets. One untrimmed video (162,000 images for 9 h) from the 14th pen was used to ultimately evaluate the action density estimation performance of the ADEN. ADEN was compared with seven approaches and its superiority was demonstrated with an r = 0.938, an RMSE = 1.080, and a MAE = 0.967 in short video clips and r = 0.982, MAE = 0.161, and RMSE = 0.563 in the untrimmed long video. The ADEN proved it feasible to predict the number of suckling events by using action density estimation." @default.
• W4375952661 created "2023-05-10" @default.
• W4375952661 creator A5006865706 @default.
• W4375952661 creator A5010766782 @default.
• W4375952661 creator A5022565684 @default.
• W4375952661 creator A5030767616 @default.
• W4375952661 creator A5038138366 @default.
• W4375952661 creator A5040976472 @default.
• W4375952661 creator A5066820736 @default.
• W4375952661 creator A5076386475 @default.
• W4375952661 creator A5089268675 @default.
• W4375952661 date "2023-07-01" @default.
• W4375952661 modified "2023-09-27" @default.
• W4375952661 title "Counting piglet suckling events using deep learning-based action density estimation" @default.
• W4375952661 cites W1849277567 @default.
• W4375952661 cites W1978275579 @default.
• W4375952661 cites W2019592567 @default.
• W4375952661 cites W2048059819 @default.
• W4375952661 cites W2083978531 @default.
• W4375952661 cites W2131019960 @default.
• W4375952661 cites W2160249880 @default.
• W4375952661 cites W2342662179 @default.
• W4375952661 cites W2463631526 @default.
• W4375952661 cites W2560498449 @default.
• W4375952661 cites W2902915203 @default.
• W4375952661 cites W2967069910 @default.
• W4375952661 cites W3007572407 @default.
• W4375952661 cites W3028219679 @default.
• W4375952661 cites W3035607189 @default.
• W4375952661 cites W3092336341 @default.
• W4375952661 cites W3153594930 @default.
• W4375952661 cites W3164897936 @default.
• W4375952661 cites W3173803963 @default.
• W4375952661 cites W3195091936 @default.
• W4375952661 cites W381581404 @default.
• W4375952661 cites W4214613509 @default.
• W4375952661 cites W4220717613 @default.
• W4375952661 cites W4229453634 @default.
• W4375952661 cites W4283705343 @default.
• W4375952661 cites W4307818729 @default.
• W4375952661 cites W4312826597 @default.
• W4375952661 doi "https://doi.org/10.1016/j.compag.2023.107877" @default.
• W4375952661 hasPublicationYear "2023" @default.
• W4375952661 type Work @default.
• W4375952661 citedByCount "0" @default.
• W4375952661 crossrefType "journal-article" @default.
• W4375952661 hasAuthorship W4375952661A5006865706 @default.
• W4375952661 hasAuthorship W4375952661A5010766782 @default.
• W4375952661 hasAuthorship W4375952661A5022565684 @default.
• W4375952661 hasAuthorship W4375952661A5030767616 @default.
• W4375952661 hasAuthorship W4375952661A5038138366 @default.
• W4375952661 hasAuthorship W4375952661A5040976472 @default.
• W4375952661 hasAuthorship W4375952661A5066820736 @default.
• W4375952661 hasAuthorship W4375952661A5076386475 @default.
• W4375952661 hasAuthorship W4375952661A5089268675 @default.
• W4375952661 hasConcept C114614502 @default.
• W4375952661 hasConcept C153180895 @default.
• W4375952661 hasConcept C154945302 @default.
• W4375952661 hasConcept C33923547 @default.
• W4375952661 hasConcept C41008148 @default.
• W4375952661 hasConcept C87619178 @default.
• W4375952661 hasConcept C97931131 @default.
• W4375952661 hasConceptScore W4375952661C114614502 @default.
• W4375952661 hasConceptScore W4375952661C153180895 @default.
• W4375952661 hasConceptScore W4375952661C154945302 @default.
• W4375952661 hasConceptScore W4375952661C33923547 @default.
• W4375952661 hasConceptScore W4375952661C41008148 @default.
• W4375952661 hasConceptScore W4375952661C87619178 @default.
• W4375952661 hasConceptScore W4375952661C97931131 @default.
• W4375952661 hasLocation W43759526611 @default.
• W4375952661 hasOpenAccess W4375952661 @default.
• W4375952661 hasPrimaryLocation W43759526611 @default.
• W4375952661 hasRelatedWork W1972656095 @default.
• W4375952661 hasRelatedWork W2024160000 @default.
• W4375952661 hasRelatedWork W2061273563 @default.
• W4375952661 hasRelatedWork W2285052147 @default.
• W4375952661 hasRelatedWork W2729514902 @default.
• W4375952661 hasRelatedWork W2743258233 @default.
• W4375952661 hasRelatedWork W2773500201 @default.
• W4375952661 hasRelatedWork W2970216048 @default.
• W4375952661 hasRelatedWork W2998168123 @default.
• W4375952661 hasRelatedWork W4287995534 @default.
• W4375952661 hasVolume "210" @default.
• W4375952661 isParatext "false" @default.
• W4375952661 isRetracted "false" @default.
• W4375952661 workType "article" @default.