Azhar, Febrian Selva (2023) PENGARUH PERUBAHAN MODEL YOLOV5 DALAM AKURASI DETEKSI EKSPESI WAJAH MENGGUNAKAN KDEF DATASET. S2 thesis, Universitas Mercu Buana - Menteng.
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Abstract
Pengenalan ekspresi wajah merupakan merupakan kecerdasan buatan yang sedang banyak dilakukan penelitian. Pengenalan ekspresi wajah digunakan untuk mengetahui keadaan emosional seseorang, baik senang, sedih, ketakutan, dan keadaan emosional lain pada manusia. kedepan nantinya penelitian pada bidang ini dapat dimanfaatkan untuk dapat digunakan dalam kehidupan manusia. Pada penelitian ini dilakukan pengenalan wajah pada dataset KDEF dengan model deteksi yolov5. dimana dataset KDEF ini terdiri dari 7 class ekspresi yaitu angry, disgust, fear, happy, neutral, sad, dan surprise dengan masing-masing class terdiri dari 420 foto. Dan yolov5 merupakan deep learning berbasis citra yang memiliki beberapa model dengan tipe konvolusi, anchor dan backbone yang berbeda. Pada penelitian ini dilakukan pembandingan model yolov5 untuk mendeteksi dataset ekspresi wajah KDEF. Sehingga akan diketahui mana model yolov5 yang paling optimal untuk digunakan pada deteksi ekspresi wajah dengan dataset KDEF. Kata kunci : Yolov5, KDEF, Ekspresi wajah Recognition of facial expressions is an artificial intelligence is being familiar for researched. Facial expression recognition used to for determine a person's emotional, like happy, sad, scared, and other emotional in human being. On the future, research in this subject can be used full in human life. In this study, facial recognition will carried out on the KDEF dataset with yolov5 detection model. where KDEF dataset consists of 7 expression classes namely angry, disgust, fear, happy, neutral, sad, and surprise with each class consisting of 420 photos. And yolov5 is an image-based deep learning that has several models with different types of convolutions, anchors and backbones. In this study, will compared between the yolov5 model to detect the KDEF facial expression dataset. So that it will be known which yolov5 model is the most optimal for use in facial expression detection with the KDEF dataset. Keyword: Yolov5, KDEF, facial expressions
| Item Type: | Thesis (S2) |
|---|---|
| NIM/NIDN Creators: | 55420120013 |
| Uncontrolled Keywords: | Yolov5, KDEF, Ekspresi wajah Yolov5, KDEF, facial expressions |
| Subjects: | 600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 621 Applied Physics/Fisika terapan |
| Divisions: | Pascasarjana > Magister Teknik Elektro |
| Depositing User: | ALFINA DHEA NOVA |
| Date Deposited: | 14 Apr 2023 04:17 |
| Last Modified: | 14 Apr 2023 04:17 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/76504 |
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