Matches in SemOpenAlex for { <https://semopenalex.org/work/W2769581371> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W2769581371 endingPage "1166" @default.
- W2769581371 startingPage "1155" @default.
- W2769581371 abstract "Recurrent neural network (RNN) and long short-term memory (LSTM) have achieved great success in processing sequential multimedia data and yielded the state-of-the-art results in speech recognition, digital signal processing, video processing, and text data analysis. In this paper, we propose a novel action recognition method by processing the video data using convolutional neural network (CNN) and deep bidirectional LSTM (DB-LSTM) network. First, deep features are extracted from every sixth frame of the videos, which helps reduce the redundancy and complexity. Next, the sequential information among frame features is learnt using DB-LSTM network, where multiple layers are stacked together in both forward pass and backward pass of DB-LSTM to increase its depth. The proposed method is capable of learning long term sequences and can process lengthy videos by analyzing features for a certain time interval. Experimental results show significant improvements in action recognition using the proposed method on three benchmark data sets including UCF-101, YouTube 11 Actions, and HMDB51 compared with the state-of-the-art action recognition methods." @default.
- W2769581371 created "2017-12-04" @default.
- W2769581371 creator A5008903140 @default.
- W2769581371 creator A5034945583 @default.
- W2769581371 creator A5052654998 @default.
- W2769581371 date "2018-01-01" @default.
- W2769581371 modified "2023-10-17" @default.
- W2769581371 title "Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features" @default.
- W2769581371 cites W1445738754 @default.
- W2769581371 cites W1689711448 @default.
- W2769581371 cites W1926645898 @default.
- W2769581371 cites W1983364832 @default.
- W2769581371 cites W2016053056 @default.
- W2769581371 cites W2028417331 @default.
- W2769581371 cites W2058580716 @default.
- W2769581371 cites W2062118960 @default.
- W2769581371 cites W2064675550 @default.
- W2769581371 cites W2098088693 @default.
- W2769581371 cites W2105101328 @default.
- W2769581371 cites W2126579184 @default.
- W2769581371 cites W2138232383 @default.
- W2769581371 cites W2143267104 @default.
- W2769581371 cites W2146634731 @default.
- W2769581371 cites W2174646748 @default.
- W2769581371 cites W2204710204 @default.
- W2769581371 cites W2322020277 @default.
- W2769581371 cites W2462496837 @default.
- W2769581371 cites W2462996230 @default.
- W2769581371 cites W2519871715 @default.
- W2769581371 cites W2594395650 @default.
- W2769581371 cites W2600446833 @default.
- W2769581371 cites W2604650092 @default.
- W2769581371 cites W2623461194 @default.
- W2769581371 cites W2672225557 @default.
- W2769581371 cites W2963218601 @default.
- W2769581371 cites W2964191259 @default.
- W2769581371 cites W2964240595 @default.
- W2769581371 cites W4249279051 @default.
- W2769581371 cites W906515803 @default.
- W2769581371 doi "https://doi.org/10.1109/access.2017.2778011" @default.
- W2769581371 hasPublicationYear "2018" @default.
- W2769581371 type Work @default.
- W2769581371 sameAs 2769581371 @default.
- W2769581371 citedByCount "479" @default.
- W2769581371 countsByYear W27695813712012 @default.
- W2769581371 countsByYear W27695813712018 @default.
- W2769581371 countsByYear W27695813712019 @default.
- W2769581371 countsByYear W27695813712020 @default.
- W2769581371 countsByYear W27695813712021 @default.
- W2769581371 countsByYear W27695813712022 @default.
- W2769581371 countsByYear W27695813712023 @default.
- W2769581371 crossrefType "journal-article" @default.
- W2769581371 hasAuthorship W2769581371A5008903140 @default.
- W2769581371 hasAuthorship W2769581371A5034945583 @default.
- W2769581371 hasAuthorship W2769581371A5052654998 @default.
- W2769581371 hasBestOaLocation W27695813711 @default.
- W2769581371 hasConcept C121332964 @default.
- W2769581371 hasConcept C153180895 @default.
- W2769581371 hasConcept C154945302 @default.
- W2769581371 hasConcept C2777212361 @default.
- W2769581371 hasConcept C2780791683 @default.
- W2769581371 hasConcept C28490314 @default.
- W2769581371 hasConcept C2987834672 @default.
- W2769581371 hasConcept C31972630 @default.
- W2769581371 hasConcept C41008148 @default.
- W2769581371 hasConcept C62520636 @default.
- W2769581371 hasConceptScore W2769581371C121332964 @default.
- W2769581371 hasConceptScore W2769581371C153180895 @default.
- W2769581371 hasConceptScore W2769581371C154945302 @default.
- W2769581371 hasConceptScore W2769581371C2777212361 @default.
- W2769581371 hasConceptScore W2769581371C2780791683 @default.
- W2769581371 hasConceptScore W2769581371C28490314 @default.
- W2769581371 hasConceptScore W2769581371C2987834672 @default.
- W2769581371 hasConceptScore W2769581371C31972630 @default.
- W2769581371 hasConceptScore W2769581371C41008148 @default.
- W2769581371 hasConceptScore W2769581371C62520636 @default.
- W2769581371 hasFunder F4320322120 @default.
- W2769581371 hasLocation W27695813711 @default.
- W2769581371 hasOpenAccess W2769581371 @default.
- W2769581371 hasPrimaryLocation W27695813711 @default.
- W2769581371 hasRelatedWork W1891287906 @default.
- W2769581371 hasRelatedWork W1969923398 @default.
- W2769581371 hasRelatedWork W1981202246 @default.
- W2769581371 hasRelatedWork W2007815619 @default.
- W2769581371 hasRelatedWork W2132186402 @default.
- W2769581371 hasRelatedWork W2726222394 @default.
- W2769581371 hasRelatedWork W2752217129 @default.
- W2769581371 hasRelatedWork W2941155331 @default.
- W2769581371 hasRelatedWork W3010888991 @default.
- W2769581371 hasRelatedWork W3106494386 @default.
- W2769581371 hasVolume "6" @default.
- W2769581371 isParatext "false" @default.
- W2769581371 isRetracted "false" @default.
- W2769581371 magId "2769581371" @default.
- W2769581371 workType "article" @default.