Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285149724> ?p ?o ?g. }
Showing items 1 to 73 of
73
with 100 items per page.
- W4285149724 abstract "Due to the poor regularization capability of single Convolutional Neural Network (CNN), the performance of face recognition system is severely affected. Also, the input facial image data for recognition is influenced by surrounding information like light, expression, brightness, contrast, pose variations and other factors. This issue is overcome by using ensemble-based feature learning ofCNN and local binary patterns (LBP). It also aids in improving the occlusion-related low pedestrian detection rate. To begin, the LBP operator is used to extract texture features from the face and by using different 10 CNN architectures, different part of facial information is learnt. This is mainly used to improve the performance of underlying networking attributes and thereby it leads to enhanced classification results using the Softmaxactivation function. With the introduced new form of face recognition focused on parallel ensemble learning of convolutional neural network and local binary pattern for feature extraction, the obtained results outperforms the existing state-of-art techniques. Finally, utilizing majority voting, the approach of parallel ensemble learning is employed to obtain the final result of face recognition. The ORL and Yale-B face datasets identification rates climb to 98.1% and 99.2 percent, respectively, for our propose system. The proposed approach is demonstrated in the experiments to improve not only the model’s immunity to withstand with different illumination, expression, lighting, brightness and posture conditions, but also the accuracy of face recognition with the poor regularization metrics, which denies in reaching the global solution in the solution space." @default.
- W4285149724 created "2022-07-14" @default.
- W4285149724 creator A5003592231 @default.
- W4285149724 creator A5040391086 @default.
- W4285149724 date "2022-01-01" @default.
- W4285149724 modified "2023-09-27" @default.
- W4285149724 title "Ensemble learning-based deep neural network model for face recognition" @default.
- W4285149724 cites W2163352848 @default.
- W4285149724 cites W2163808566 @default.
- W4285149724 cites W2183341477 @default.
- W4285149724 cites W2194775991 @default.
- W4285149724 cites W2782874754 @default.
- W4285149724 cites W2794741626 @default.
- W4285149724 cites W2908741115 @default.
- W4285149724 cites W2916976239 @default.
- W4285149724 cites W3039081519 @default.
- W4285149724 doi "https://doi.org/10.1063/5.0080415" @default.
- W4285149724 hasPublicationYear "2022" @default.
- W4285149724 type Work @default.
- W4285149724 citedByCount "1" @default.
- W4285149724 countsByYear W42851497242023 @default.
- W4285149724 crossrefType "proceedings-article" @default.
- W4285149724 hasAuthorship W4285149724A5003592231 @default.
- W4285149724 hasAuthorship W4285149724A5040391086 @default.
- W4285149724 hasBestOaLocation W42851497241 @default.
- W4285149724 hasConcept C108583219 @default.
- W4285149724 hasConcept C115961682 @default.
- W4285149724 hasConcept C144024400 @default.
- W4285149724 hasConcept C153180895 @default.
- W4285149724 hasConcept C154945302 @default.
- W4285149724 hasConcept C2776135515 @default.
- W4285149724 hasConcept C2779304628 @default.
- W4285149724 hasConcept C31510193 @default.
- W4285149724 hasConcept C31972630 @default.
- W4285149724 hasConcept C36289849 @default.
- W4285149724 hasConcept C41008148 @default.
- W4285149724 hasConcept C52622490 @default.
- W4285149724 hasConcept C53533937 @default.
- W4285149724 hasConcept C81363708 @default.
- W4285149724 hasConcept C83665646 @default.
- W4285149724 hasConcept C87335442 @default.
- W4285149724 hasConceptScore W4285149724C108583219 @default.
- W4285149724 hasConceptScore W4285149724C115961682 @default.
- W4285149724 hasConceptScore W4285149724C144024400 @default.
- W4285149724 hasConceptScore W4285149724C153180895 @default.
- W4285149724 hasConceptScore W4285149724C154945302 @default.
- W4285149724 hasConceptScore W4285149724C2776135515 @default.
- W4285149724 hasConceptScore W4285149724C2779304628 @default.
- W4285149724 hasConceptScore W4285149724C31510193 @default.
- W4285149724 hasConceptScore W4285149724C31972630 @default.
- W4285149724 hasConceptScore W4285149724C36289849 @default.
- W4285149724 hasConceptScore W4285149724C41008148 @default.
- W4285149724 hasConceptScore W4285149724C52622490 @default.
- W4285149724 hasConceptScore W4285149724C53533937 @default.
- W4285149724 hasConceptScore W4285149724C81363708 @default.
- W4285149724 hasConceptScore W4285149724C83665646 @default.
- W4285149724 hasConceptScore W4285149724C87335442 @default.
- W4285149724 hasLocation W42851497241 @default.
- W4285149724 hasOpenAccess W4285149724 @default.
- W4285149724 hasPrimaryLocation W42851497241 @default.
- W4285149724 hasRelatedWork W1771356744 @default.
- W4285149724 hasRelatedWork W1775397219 @default.
- W4285149724 hasRelatedWork W2118573226 @default.
- W4285149724 hasRelatedWork W2207021851 @default.
- W4285149724 hasRelatedWork W2486556835 @default.
- W4285149724 hasRelatedWork W2532679621 @default.
- W4285149724 hasRelatedWork W2764305069 @default.
- W4285149724 hasRelatedWork W2772780115 @default.
- W4285149724 hasRelatedWork W2897995864 @default.
- W4285149724 hasRelatedWork W2914194627 @default.
- W4285149724 isParatext "false" @default.
- W4285149724 isRetracted "false" @default.
- W4285149724 workType "article" @default.