Matches in SemOpenAlex for { <https://semopenalex.org/work/W3004826650> ?p ?o ?g. }
Showing items 1 to 95 of
95
with 100 items per page.
- W3004826650 endingPage "1387" @default.
- W3004826650 startingPage "1375" @default.
- W3004826650 abstract "Railway shunting accidents, in which trains collide with obstacles, often occur because of human error or fatigue. It is therefore necessary to detect traffic objects in front of the trains and inform the driver to take timely action. To detect these objects in railways, we proposed an object-detection method using a differential feature fusion convolutional neural network (DFF-Net). DFF-Net includes two modules: the prior object-detection module and the object-detection module. The prior module produces initial anchor boxes for the subsequent detection module. Taking the initial anchor boxes as input, the object-detection module applies a differential feature fusion sub-module to enrich the sematic information for object detection, enhancing the detection performance, particularly for small objects. In experiments conducted on a railway traffic dataset, compared with the current state-of-the-art detectors, the proposed method exhibited significant higher performance and was more effective and more efficient than the other methods for object detection in railway tracks. Additionally, evaluation results based on PASCAL VOC2007 and VOC2012 indicated that the proposed method was significantly better than the state-of-the-art methods." @default.
- W3004826650 created "2020-02-14" @default.
- W3004826650 creator A5012440924 @default.
- W3004826650 creator A5031587262 @default.
- W3004826650 creator A5064354572 @default.
- W3004826650 creator A5070538645 @default.
- W3004826650 date "2021-03-01" @default.
- W3004826650 modified "2023-10-16" @default.
- W3004826650 title "Railway Traffic Object Detection Using Differential Feature Fusion Convolution Neural Network" @default.
- W3004826650 cites W1536680647 @default.
- W3004826650 cites W2047629720 @default.
- W3004826650 cites W2091622218 @default.
- W3004826650 cites W2094263170 @default.
- W3004826650 cites W2097117768 @default.
- W3004826650 cites W2109255472 @default.
- W3004826650 cites W2126516862 @default.
- W3004826650 cites W2131076267 @default.
- W3004826650 cites W2157745573 @default.
- W3004826650 cites W2165035808 @default.
- W3004826650 cites W2176950688 @default.
- W3004826650 cites W2194775991 @default.
- W3004826650 cites W2249868474 @default.
- W3004826650 cites W2326558644 @default.
- W3004826650 cites W2519371714 @default.
- W3004826650 cites W2565639579 @default.
- W3004826650 cites W2773776445 @default.
- W3004826650 cites W2808267564 @default.
- W3004826650 cites W2899526967 @default.
- W3004826650 cites W2919115771 @default.
- W3004826650 cites W2962917547 @default.
- W3004826650 cites W2963037989 @default.
- W3004826650 cites W639708223 @default.
- W3004826650 doi "https://doi.org/10.1109/tits.2020.2969993" @default.
- W3004826650 hasPublicationYear "2021" @default.
- W3004826650 type Work @default.
- W3004826650 sameAs 3004826650 @default.
- W3004826650 citedByCount "36" @default.
- W3004826650 countsByYear W30048266502020 @default.
- W3004826650 countsByYear W30048266502021 @default.
- W3004826650 countsByYear W30048266502022 @default.
- W3004826650 countsByYear W30048266502023 @default.
- W3004826650 crossrefType "journal-article" @default.
- W3004826650 hasAuthorship W3004826650A5012440924 @default.
- W3004826650 hasAuthorship W3004826650A5031587262 @default.
- W3004826650 hasAuthorship W3004826650A5064354572 @default.
- W3004826650 hasAuthorship W3004826650A5070538645 @default.
- W3004826650 hasConcept C138885662 @default.
- W3004826650 hasConcept C153180895 @default.
- W3004826650 hasConcept C154945302 @default.
- W3004826650 hasConcept C158525013 @default.
- W3004826650 hasConcept C2776151529 @default.
- W3004826650 hasConcept C2776401178 @default.
- W3004826650 hasConcept C31972630 @default.
- W3004826650 hasConcept C33954974 @default.
- W3004826650 hasConcept C41008148 @default.
- W3004826650 hasConcept C41895202 @default.
- W3004826650 hasConcept C45347329 @default.
- W3004826650 hasConcept C50644808 @default.
- W3004826650 hasConcept C52622490 @default.
- W3004826650 hasConcept C81363708 @default.
- W3004826650 hasConceptScore W3004826650C138885662 @default.
- W3004826650 hasConceptScore W3004826650C153180895 @default.
- W3004826650 hasConceptScore W3004826650C154945302 @default.
- W3004826650 hasConceptScore W3004826650C158525013 @default.
- W3004826650 hasConceptScore W3004826650C2776151529 @default.
- W3004826650 hasConceptScore W3004826650C2776401178 @default.
- W3004826650 hasConceptScore W3004826650C31972630 @default.
- W3004826650 hasConceptScore W3004826650C33954974 @default.
- W3004826650 hasConceptScore W3004826650C41008148 @default.
- W3004826650 hasConceptScore W3004826650C41895202 @default.
- W3004826650 hasConceptScore W3004826650C45347329 @default.
- W3004826650 hasConceptScore W3004826650C50644808 @default.
- W3004826650 hasConceptScore W3004826650C52622490 @default.
- W3004826650 hasConceptScore W3004826650C81363708 @default.
- W3004826650 hasIssue "3" @default.
- W3004826650 hasLocation W30048266501 @default.
- W3004826650 hasOpenAccess W3004826650 @default.
- W3004826650 hasPrimaryLocation W30048266501 @default.
- W3004826650 hasRelatedWork W2059299633 @default.
- W3004826650 hasRelatedWork W2296151615 @default.
- W3004826650 hasRelatedWork W2732542196 @default.
- W3004826650 hasRelatedWork W2760011800 @default.
- W3004826650 hasRelatedWork W2760085659 @default.
- W3004826650 hasRelatedWork W2913302899 @default.
- W3004826650 hasRelatedWork W2977314777 @default.
- W3004826650 hasRelatedWork W2995914718 @default.
- W3004826650 hasRelatedWork W3081496756 @default.
- W3004826650 hasRelatedWork W3156786002 @default.
- W3004826650 hasVolume "22" @default.
- W3004826650 isParatext "false" @default.
- W3004826650 isRetracted "false" @default.
- W3004826650 magId "3004826650" @default.
- W3004826650 workType "article" @default.