Matches in SemOpenAlex for { <https://semopenalex.org/work/W4360994426> ?p ?o ?g. }
Showing items 1 to 88 of
88
with 100 items per page.
- W4360994426 abstract "Facial Emotion Recognition System is one of the emerging technologies and it has been a quite challenging task to recognize the human facial expressions using computer algorithms in emotion analysis rather than the humans. In human’s ideology, facial expressions like sorrowful, joyful, frightened, anger, disgust are assumed as a fundamental part. The main objective of Facial emotion Recognition System research is to focus on the traits of people with criminal associations facial expressions. As the traditional algorithms haven’t met the human needs, where Machine learning and deep learning algorithms have gained great success. There are many techniques applied to gain efficient results in identifying facial expressions for Human-machine interaction, monitoring security and treating patients in the medical field are some of the applications of facial expression recognition. So, it is necessary to build a model-based system to understand human emotions in different scenarios. The Convolutional Neural Network (CNN) algorithm is used to know the facial expressions of humans. On this framework, the CNN layers are upgraded, and the LBP is incorporated with it to merge multiple networking algorithms to develop the human emotion model. In the end, to check the validity of the new technique, CNNLBP is implemented. The experimental result show that accuracy of emotion recognition in between the training and testing phases, the CNNLBP model achieves an average accuracy of 98.3% compared to other traditional models." @default.
- W4360994426 created "2023-03-30" @default.
- W4360994426 creator A5001783662 @default.
- W4360994426 creator A5007090798 @default.
- W4360994426 creator A5038185966 @default.
- W4360994426 creator A5063470257 @default.
- W4360994426 creator A5074068416 @default.
- W4360994426 creator A5086174845 @default.
- W4360994426 date "2023-02-02" @default.
- W4360994426 modified "2023-10-01" @default.
- W4360994426 title "Hybrid CNNLBP using Facial Emotion Recognition based on Deep Learning Approach" @default.
- W4360994426 cites W1934410531 @default.
- W4360994426 cites W2096044434 @default.
- W4360994426 cites W2253728219 @default.
- W4360994426 cites W2277498883 @default.
- W4360994426 cites W2775234439 @default.
- W4360994426 cites W2796830519 @default.
- W4360994426 cites W2903473981 @default.
- W4360994426 cites W2918378401 @default.
- W4360994426 cites W2976153122 @default.
- W4360994426 cites W3017822820 @default.
- W4360994426 cites W3119213473 @default.
- W4360994426 cites W3121847537 @default.
- W4360994426 cites W4316021163 @default.
- W4360994426 doi "https://doi.org/10.1109/icais56108.2023.10073918" @default.
- W4360994426 hasPublicationYear "2023" @default.
- W4360994426 type Work @default.
- W4360994426 citedByCount "2" @default.
- W4360994426 countsByYear W43609944262023 @default.
- W4360994426 crossrefType "proceedings-article" @default.
- W4360994426 hasAuthorship W4360994426A5001783662 @default.
- W4360994426 hasAuthorship W4360994426A5007090798 @default.
- W4360994426 hasAuthorship W4360994426A5038185966 @default.
- W4360994426 hasAuthorship W4360994426A5063470257 @default.
- W4360994426 hasAuthorship W4360994426A5074068416 @default.
- W4360994426 hasAuthorship W4360994426A5086174845 @default.
- W4360994426 hasConcept C108583219 @default.
- W4360994426 hasConcept C118552586 @default.
- W4360994426 hasConcept C119857082 @default.
- W4360994426 hasConcept C153180895 @default.
- W4360994426 hasConcept C154945302 @default.
- W4360994426 hasConcept C15744967 @default.
- W4360994426 hasConcept C195704467 @default.
- W4360994426 hasConcept C197129107 @default.
- W4360994426 hasConcept C206310091 @default.
- W4360994426 hasConcept C23123220 @default.
- W4360994426 hasConcept C2777375102 @default.
- W4360994426 hasConcept C2777438025 @default.
- W4360994426 hasConcept C2779302386 @default.
- W4360994426 hasConcept C28490314 @default.
- W4360994426 hasConcept C31510193 @default.
- W4360994426 hasConcept C41008148 @default.
- W4360994426 hasConcept C50644808 @default.
- W4360994426 hasConcept C81363708 @default.
- W4360994426 hasConceptScore W4360994426C108583219 @default.
- W4360994426 hasConceptScore W4360994426C118552586 @default.
- W4360994426 hasConceptScore W4360994426C119857082 @default.
- W4360994426 hasConceptScore W4360994426C153180895 @default.
- W4360994426 hasConceptScore W4360994426C154945302 @default.
- W4360994426 hasConceptScore W4360994426C15744967 @default.
- W4360994426 hasConceptScore W4360994426C195704467 @default.
- W4360994426 hasConceptScore W4360994426C197129107 @default.
- W4360994426 hasConceptScore W4360994426C206310091 @default.
- W4360994426 hasConceptScore W4360994426C23123220 @default.
- W4360994426 hasConceptScore W4360994426C2777375102 @default.
- W4360994426 hasConceptScore W4360994426C2777438025 @default.
- W4360994426 hasConceptScore W4360994426C2779302386 @default.
- W4360994426 hasConceptScore W4360994426C28490314 @default.
- W4360994426 hasConceptScore W4360994426C31510193 @default.
- W4360994426 hasConceptScore W4360994426C41008148 @default.
- W4360994426 hasConceptScore W4360994426C50644808 @default.
- W4360994426 hasConceptScore W4360994426C81363708 @default.
- W4360994426 hasLocation W43609944261 @default.
- W4360994426 hasOpenAccess W4360994426 @default.
- W4360994426 hasPrimaryLocation W43609944261 @default.
- W4360994426 hasRelatedWork W1974787498 @default.
- W4360994426 hasRelatedWork W1987293618 @default.
- W4360994426 hasRelatedWork W2062652500 @default.
- W4360994426 hasRelatedWork W2119012436 @default.
- W4360994426 hasRelatedWork W2163750407 @default.
- W4360994426 hasRelatedWork W2947045439 @default.
- W4360994426 hasRelatedWork W3167551411 @default.
- W4360994426 hasRelatedWork W3180630304 @default.
- W4360994426 hasRelatedWork W4220769512 @default.
- W4360994426 hasRelatedWork W4316021163 @default.
- W4360994426 isParatext "false" @default.
- W4360994426 isRetracted "false" @default.
- W4360994426 workType "article" @default.