Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze
<p dir="ltr">The recent advancement of Artificial Intelligence (AI) affords ambition to exploit this revolution in multiple fields. Computer-assisted teaching and learning creates a very important area of AI application. Consequently, this last will be able to revolutionize this fiel...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2022
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1864513518575812608 |
|---|---|
| author | N. El Bahri (18295363) |
| author2 | Z. Itahriouan (18295366) S. Brahim Belhaouari (18295369) A. Abtoy (18295372) |
| author2_role | author author author |
| author_facet | N. El Bahri (18295363) Z. Itahriouan (18295366) S. Brahim Belhaouari (18295369) A. Abtoy (18295372) |
| author_role | author |
| dc.creator.none.fl_str_mv | N. El Bahri (18295363) Z. Itahriouan (18295366) S. Brahim Belhaouari (18295369) A. Abtoy (18295372) |
| dc.date.none.fl_str_mv | 2022-05-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1051/e3sconf/202235101032 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Using_Deep_Learning_to_detect_Facial_Expression_from_front_camera_Towards_students_interactions_analyze/25532932 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Education Specialist studies in education Information and computing sciences Artificial intelligence Computer vision and multimedia computation Machine learning Deep Learning Artificial Neural Network Computer Vision Emotion Detection |
| dc.title.none.fl_str_mv | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The recent advancement of Artificial Intelligence (AI) affords ambition to exploit this revolution in multiple fields. Computer-assisted teaching and learning creates a very important area of AI application. Consequently, this last will be able to revolutionize this field. In research conducted by our laboratory, we are interested to explore AI trends to teaching and learning technologies. As part of this, we aim to study learner’s behaviors in education and learning environment, thus we aim to analyze the student through the front camera, as a first step we intend to develop a model that classify face’s images based on deep learning and Convolutional Neural Networks (CNN) in particular. Model development of images classification can be realized based in several technologies, we have chosen for this study to use IBM solutions, which are provided on the cloud. This paper describes the training experiment and the model development based on two alternatives proposed by IBM where the goal is to generate the most precise model. It presents a comparative study between the two approaches and ends with result discussing and the choice of the accurate solution for deployment in our teaching and learning system.</p><h2>Other Information</h2><p dir="ltr">Published in: E3S Web of Conferences<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1051/e3sconf/202235101032" target="_blank">https://dx.doi.org/10.1051/e3sconf/202235101032</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_c9104fc14c6c22243e985c4172559f7f |
| identifier_str_mv | 10.1051/e3sconf/202235101032 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25532932 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyzeN. El Bahri (18295363)Z. Itahriouan (18295366)S. Brahim Belhaouari (18295369)A. Abtoy (18295372)EducationSpecialist studies in educationInformation and computing sciencesArtificial intelligenceComputer vision and multimedia computationMachine learningDeep LearningArtificial Neural NetworkComputer VisionEmotion Detection<p dir="ltr">The recent advancement of Artificial Intelligence (AI) affords ambition to exploit this revolution in multiple fields. Computer-assisted teaching and learning creates a very important area of AI application. Consequently, this last will be able to revolutionize this field. In research conducted by our laboratory, we are interested to explore AI trends to teaching and learning technologies. As part of this, we aim to study learner’s behaviors in education and learning environment, thus we aim to analyze the student through the front camera, as a first step we intend to develop a model that classify face’s images based on deep learning and Convolutional Neural Networks (CNN) in particular. Model development of images classification can be realized based in several technologies, we have chosen for this study to use IBM solutions, which are provided on the cloud. This paper describes the training experiment and the model development based on two alternatives proposed by IBM where the goal is to generate the most precise model. It presents a comparative study between the two approaches and ends with result discussing and the choice of the accurate solution for deployment in our teaching and learning system.</p><h2>Other Information</h2><p dir="ltr">Published in: E3S Web of Conferences<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1051/e3sconf/202235101032" target="_blank">https://dx.doi.org/10.1051/e3sconf/202235101032</a></p>2022-05-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1051/e3sconf/202235101032https://figshare.com/articles/journal_contribution/Using_Deep_Learning_to_detect_Facial_Expression_from_front_camera_Towards_students_interactions_analyze/25532932CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/255329322022-05-01T00:00:00Z |
| spellingShingle | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze N. El Bahri (18295363) Education Specialist studies in education Information and computing sciences Artificial intelligence Computer vision and multimedia computation Machine learning Deep Learning Artificial Neural Network Computer Vision Emotion Detection |
| status_str | publishedVersion |
| title | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze |
| title_full | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze |
| title_fullStr | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze |
| title_full_unstemmed | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze |
| title_short | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze |
| title_sort | Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze |
| topic | Education Specialist studies in education Information and computing sciences Artificial intelligence Computer vision and multimedia computation Machine learning Deep Learning Artificial Neural Network Computer Vision Emotion Detection |