Matches in SemOpenAlex for { <https://semopenalex.org/work/W2991978568> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W2991978568 endingPage "1487" @default.
- W2991978568 startingPage "1487" @default.
- W2991978568 abstract "Automatic facial expression recognition is an emerging field. Moreover, the interest has been increased with the transition from laboratory-controlled conditions to in the wild scenarios. Most of the research has been done over nonoccluded faces under the constrained environment, while automatic facial expression is less understood/implemented for partial occlusion in the real world conditions. Apart from that, our research aims to tackle the issues of overfitting (caused by the shortage of adequate training data) and to alleviate the expression-unrelated/intraclass/nonlinear facial variations, such as head pose estimation, eye gaze estimation, intensity and microexpressions. In our research, we control the magnitude of each Action Unit (AU) and combine several of the Action Unit combinations to leverage learning from the generative and discriminative representations for automatic FER. We have also addressed the problem of diversification of expressions from lab controlled to real-world scenarios from our cross-database study and proposed a model for enhancement of the discriminative power of deep features while increasing the interclass scatters, by preserving the locality closeness. Furthermore, facial expression consists of an expressive component as well as neutral component, so we proposed a generative model which is capable of generating neutral expression from an input image using cGAN. The expressive component is filtered and passed to the intermediate layers and the process is called De-expression Residue Learning. The residue in the intermediate/middle layers is very important for learning through expressive components. Finally, we validate the effectiveness of our method (DLP-DeRL) through qualitative and quantitative experimental results using four databases. Our method is more accurate and robust, and outperforms all the existing methods (hand crafted features and deep learning) while dealing the images in the wild." @default.
- W2991978568 created "2019-12-13" @default.
- W2991978568 creator A5003135737 @default.
- W2991978568 creator A5005456828 @default.
- W2991978568 creator A5010989487 @default.
- W2991978568 creator A5014296507 @default.
- W2991978568 creator A5053001616 @default.
- W2991978568 creator A5088732435 @default.
- W2991978568 date "2019-12-06" @default.
- W2991978568 modified "2023-09-26" @default.
- W2991978568 title "Facial Expression Recognition of Nonlinear Facial Variations Using Deep Locality De-Expression Residue Learning in the Wild" @default.
- W2991978568 cites W1040410175 @default.
- W2991978568 cites W1967022116 @default.
- W2991978568 cites W1970942140 @default.
- W2991978568 cites W2001290948 @default.
- W2991978568 cites W2035372623 @default.
- W2991978568 cites W2086944309 @default.
- W2991978568 cites W2129812935 @default.
- W2991978568 cites W2139916508 @default.
- W2991978568 cites W2144764737 @default.
- W2991978568 cites W2506506742 @default.
- W2991978568 cites W2888037738 @default.
- W2991978568 cites W2904483377 @default.
- W2991978568 cites W2962716958 @default.
- W2991978568 cites W2963410617 @default.
- W2991978568 cites W2969647369 @default.
- W2991978568 cites W3124675547 @default.
- W2991978568 doi "https://doi.org/10.3390/electronics8121487" @default.
- W2991978568 hasPublicationYear "2019" @default.
- W2991978568 type Work @default.
- W2991978568 sameAs 2991978568 @default.
- W2991978568 citedByCount "6" @default.
- W2991978568 countsByYear W29919785682019 @default.
- W2991978568 countsByYear W29919785682021 @default.
- W2991978568 countsByYear W29919785682022 @default.
- W2991978568 crossrefType "journal-article" @default.
- W2991978568 hasAuthorship W2991978568A5003135737 @default.
- W2991978568 hasAuthorship W2991978568A5005456828 @default.
- W2991978568 hasAuthorship W2991978568A5010989487 @default.
- W2991978568 hasAuthorship W2991978568A5014296507 @default.
- W2991978568 hasAuthorship W2991978568A5053001616 @default.
- W2991978568 hasAuthorship W2991978568A5088732435 @default.
- W2991978568 hasBestOaLocation W29919785681 @default.
- W2991978568 hasConcept C108583219 @default.
- W2991978568 hasConcept C119857082 @default.
- W2991978568 hasConcept C138885662 @default.
- W2991978568 hasConcept C153180895 @default.
- W2991978568 hasConcept C154945302 @default.
- W2991978568 hasConcept C195704467 @default.
- W2991978568 hasConcept C199360897 @default.
- W2991978568 hasConcept C22019652 @default.
- W2991978568 hasConcept C2779808786 @default.
- W2991978568 hasConcept C28490314 @default.
- W2991978568 hasConcept C31972630 @default.
- W2991978568 hasConcept C41008148 @default.
- W2991978568 hasConcept C41895202 @default.
- W2991978568 hasConcept C50644808 @default.
- W2991978568 hasConcept C90559484 @default.
- W2991978568 hasConcept C97931131 @default.
- W2991978568 hasConceptScore W2991978568C108583219 @default.
- W2991978568 hasConceptScore W2991978568C119857082 @default.
- W2991978568 hasConceptScore W2991978568C138885662 @default.
- W2991978568 hasConceptScore W2991978568C153180895 @default.
- W2991978568 hasConceptScore W2991978568C154945302 @default.
- W2991978568 hasConceptScore W2991978568C195704467 @default.
- W2991978568 hasConceptScore W2991978568C199360897 @default.
- W2991978568 hasConceptScore W2991978568C22019652 @default.
- W2991978568 hasConceptScore W2991978568C2779808786 @default.
- W2991978568 hasConceptScore W2991978568C28490314 @default.
- W2991978568 hasConceptScore W2991978568C31972630 @default.
- W2991978568 hasConceptScore W2991978568C41008148 @default.
- W2991978568 hasConceptScore W2991978568C41895202 @default.
- W2991978568 hasConceptScore W2991978568C50644808 @default.
- W2991978568 hasConceptScore W2991978568C90559484 @default.
- W2991978568 hasConceptScore W2991978568C97931131 @default.
- W2991978568 hasIssue "12" @default.
- W2991978568 hasLocation W29919785681 @default.
- W2991978568 hasOpenAccess W2991978568 @default.
- W2991978568 hasPrimaryLocation W29919785681 @default.
- W2991978568 hasRelatedWork W2035372623 @default.
- W2991978568 hasRelatedWork W2285052147 @default.
- W2991978568 hasRelatedWork W2353457699 @default.
- W2991978568 hasRelatedWork W2407142979 @default.
- W2991978568 hasRelatedWork W2766123424 @default.
- W2991978568 hasRelatedWork W3018375584 @default.
- W2991978568 hasRelatedWork W3099765033 @default.
- W2991978568 hasRelatedWork W3186919929 @default.
- W2991978568 hasRelatedWork W4361732492 @default.
- W2991978568 hasRelatedWork W4362499066 @default.
- W2991978568 hasVolume "8" @default.
- W2991978568 isParatext "false" @default.
- W2991978568 isRetracted "false" @default.
- W2991978568 magId "2991978568" @default.
- W2991978568 workType "article" @default.