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Journal : KLIK: Kajian Ilmiah Informatika dan Komputer

Enhanced Facial Expression Recognition Through a Hybrid Deep Learning Approach Combining ResNet50 and ResNet34 Models Auliana, Sigit; Mahrojah, Siti; Aryono, Gagah Dwiki Putra
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1874

Abstract

Recognizing facial expressions is a critical aspect of computer vision and human-computer interaction. It facilitates the interpretation of human emotions from facial images, aiding in applications such as affective computing, social robotics, and psychological research. In this work, we propose using hybrid deep learning models, ResNet50 and ResNet34, for facial expression classification. These models, pre-trained on large-scale datasets, demonstrate exceptional feature extraction capabilities and have achieved excellent performance in various computer vision tasks. Our approach begins with the collection and preprocessing of a labeled facial expression dataset. The collected data undergoes face detection, alignment, and normalization to ensure consistency and reduce noise. After preprocessing, the dataset is divided into training, validation, and testing sets. We fine-tune the ResNet50 and ResNet34 models on the training set, employing transfer learning to adapt the pre-trained models specifically for the facial expression recognition task. Optimization techniques such as SGDM, ADAM, and RMSprop are used to update the models' parameters and minimize the categorical cross-entropy loss function. The trained models are evaluated on the validation set, achieving an accuracy of 98.19%. Subsequently, the models are tested on unseen facial images to assess their generalization capabilities. This proposed approach aims to deliver accurate and robust facial expression classification, thereby advancing emotion analysis and human-computer interaction systems.
Multi-Domain Medical Image Enhancement Through Fuzzy and Regression Neural Network Approach Auliana, Sigit; Nur Janah, Meishi; Gagah Dwiki Putra Aryono
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1875

Abstract

Medical image processing has heralded a significant transformation in contemporary medical science, offering the promise of diagnosing, treating, and curing patients while minimizing adverse effects. By leveraging medical imaging, physicians gain the ability to visualize internal structures without invasive procedures. Moreover, this technology contributes to our understanding of neurobiology and human behavior, with brain imaging aiding investigations into addiction mechanisms. Interdisciplinary collaboration among biologists, chemists, and physicists is facilitated by medical imaging, with resultant technologies finding applications across various fields. This study focuses on enhancing medical images in both frequency and time domains. Contrast enhancement is achieved through local transformation histogram techniques, followed by overall enhancement using a Fuzzy-Neural approach. The proposed methodology is implemented using MATLAB 2018b. The findings emphasize the efficacy of the proposed technique in improving image quality for both MR and Selenography images. Its outstanding performance, marked by a higher PSNR (32.96) and a lower MSE (20.04), indicates its potential for more precise and dependable image enhancement compared to current methods.
Co-Authors A Halim Achmad Dwi Saputro Achmad Dwi Saputro Ahmad Andika Mulyawansyah Ahmad Munawir Alandito, Alhdias Aldi Setiawan, Aldi Aldiyanti, Fitri Ali Rohman Ali Rohman Alia, Salsabila Rahma Anam, Aan Khoirul Anggi Nur Aisah Anti Restiana Anugerah Agung ardiansyah, sigit Ariansyah, Irgi Asep Darma Nugraha Asep Safaatullah Asep Sapaatullah ASNAWI Audina, Alisa Bafaqih, Ali Basuki Permana Basuki Rakhim Setya Permana Cahyadi, Wahyu Chafid, Nurul Dadan Ramdan DEWI FITRIANI Dio Falla Arrasit Dwi Purnama, Eris Eightian, Vieri Ginola Ende Ende Ende Eris Dwi Purnama Eris Dwi Purnama Fachruroji, Fahmi Fadia Syifa Maulida Fajri Fatullah Fanani, Khairul Fasya, Nabiila Fatari Ferawati, Dede Fipi Andriani Furtasan Ali Yusuf Gagah Dwiki Putra Aryanto Gagah Dwiki Putra Aryono Gelard Untirtha Pratama Hadi Kurniawanto Hadi Ramadhan, Muhamad Hadisuwarno, Noppy Hamdan Hamdan Hamdan Hamdan Hamidah . Hamidah Hamidah Ibrohim Ibrohim Ifvochy, Jammes Iis Nuraisah Iis Nurasiah Iis Nurasiah Ilham, Ilham Rizqi Irfansyah, Robby Jaka Wijaya Kusuma Jalis, Jalis Kalsum, Ummy Kiki Nabilah Pusvita Oula Kustianto, Prahmono Laila Nur Fadhilah Laksono Trisnantoro Listiawati Listiawati Mahrojah, Siti Maman Masyhuri Maman Masyhuri Mamay Komarudin Marisa Azis Maulana Ns, Farhan Miftahul Rizki MMSI Irfan ,S. Kom Mochammad Darip Muchtadi, R. Hudan Mudofar, Mudofar Muhamadin, Ari Muhammad Rifda Sholahuddin Muhammad Saifulloh Munawaroh Munawaroh Munawir, Ahmad Naufal Affandi Naufal, Dody Naufallinho, Muchamad Khairan Ningsih, Ratu Septia Nitami, Shella Nopfitasari, Nopfitasari Nopithasari, Lola Nova, Merlin Dwi Novita Sari Noviyanti, Ayu Nugraha Edhi Suyatma Nugrahini Kusumawati Nuniek Permata Nur Janah, Meishi Nurfitrianda, Deden Nursafira, Nursafira Nurul Chafid Nurul Chapid Nurul Khoer Hidayah, Nadaa Octavian, Rizqi Kevin Oki Firmansyah Parimin Permata, Nuniek Praditya, Dinar Okto Purnama, Eris Dwi Putra, Abraham Rahadian Arief Rakhim, Basuki Rizki Ramadhan rohaimudin, iim Rohman, Itqu Romayasari, Vera Romli, Ombi Sabilillah, Sahrul Safaatulloh, Asep Safitri, Esti Salehah, Siti Nur Saniyyasyah, Dinar Jauzaa Saputro, Ahmad Dwi Setya Permana, Basuki Rakhim Setya, Basuki Rakhim Siti Fatonah Siti Fatonah Sopian Sopian Suaryo, Suaryo Suhandi Suhandi Suhandi Suhandi, Suhandi Sunardi Sunardi Sunardi Surachman Surachman Suyatma, Nugraha Edi Syamil Basayev, Gito Tabroni Tjahja Muhandri Ubaedilah, Ikbal Umar Mansyuri Untirtha Pratama, Gelard Wahyu Amaldi Wahyu Saputra Yansyah, Mardi Yustiana, Sisy Zahra, Surti