Skripsi

SISTEM PENDETEKSIAN EMOSI MULTI-WAJAH MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN)

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Penilaian

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This research aims to develop and implement a real-time multi-face detection and emotion recognition system. The Haar Cascade method is used in the face detection stage to identify the position of faces in the image, while the Convolutional Neural Network (CNN) is used in the emotion classification stage based on the detected faces. The datasets used include FDDB for face detection testing and FER-2013 for emotion classification testing. The results of multi-face detection testing using Haar Cascade on a subset of FDDB showed an accuracy of 63%. Emotion classification testing using CNN on the FER-2013 dataset resulted in an accuracy of 74%. The overall success rate of the application was calculated, resulting in a value of 47%. Based on these results, the system is capable of performing real-time multi-face detection and emotion classification with a moderate success rate and still has room for improvement, especially in the multi-face detection stage

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507005495	T183263	T1832632025	Central Library (Referensi)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1832632025

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xxi, 358 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Teknik Informatika

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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