Perbandingan Dataset Labelled Faces in the Wild (LFW) dan faces94 Menggunakan Algoritma Convolutional Neural Networks (CNN) untuk Pengenalan Wajah

  • Indra Sari Kusuma Wardhana Universitas Indraprasta PGRI, Jakarta
  • Widi Hastomo Institut Teknologi dan Bisnis Ahmad Dahlan, Jakarta
Keywords: Perbandingan, LFW, faces94, CNN, VGG16

Abstract

This research compares the performance of two popular datasets, Labelled Faces in the Wild (LFW) and faces94, in the task of face recognition using Convolutional Neural Networks (CNN) algorithms. The LFW dataset is known for its high variation in pose, lighting, and expression, while faces94 is more structured with more uniform lighting and pose conditions. CNNs were chosen for their ability to extract important features from face images for classification. In this study, a CNN model was trained on both datasets and its performance was evaluated using accuracy, precision, and recall metrics. The experimental results showed that the model trained on the faces94 dataset achieved higher accuracy compared to the model trained on the LFW dataset. However, the model on the LFW dataset demonstrated better resilience to variations in lighting and pose conditions. These findings indicate that while a more structured dataset like faces94 can produce a model with high accuracy under testing conditions similar to the training data, a dataset with greater variation like LFW is more suitable for real-world applications involving diverse conditions. This study provides important insights into the selection of datasets for developing robust and accurate face recognition systems.

References

Ari Hadhiwibowo, Sukma Ramadhan Asri, Rika Andriyanti Dinata. 2024. Penerapan Convolutional Neural Network dengan Arsitektur Mobilenetv2 Pada Aplikasi Penerjemah dan Pembelajaran Bahasa Isyarat. Terapan Informatika Nusantara. Januari. Simpang Limun. Medan. Sumatera Utara.

Mohammad Ushuludin, Sam Farisa Chairul Haviana, I. Subroto. Sistem Deteksi Masker pada Wajah Menggunakan Convolutional Neural Network Arsitektur VGG16. TRANSMISI: Jurnal Ilmiah Teknik Elektro Vol 25, No.4 (2023): 179-185.

Hyeongjin Kim, Jong-Ha Lee, Byoung Chul Ko. Facial Expression Recognition in the Wild Using Face Graph and Attention. IEEE Access Vol. 11, 2023: 59774-59787.

Meghana P G, Mohammad Yusuf Khan, Mahesh Bharti, Kalpesh Mohanta, Kanaiya V K. Facial Emotion Recognition using CNN. Journal of Advanced Zoology Vol. 44, Issue S-6 Year 2023. Hal. 966-970
Published
2024-07-16
How to Cite
Indra Sari Kusuma Wardhana, & Widi Hastomo. (2024). Perbandingan Dataset Labelled Faces in the Wild (LFW) dan faces94 Menggunakan Algoritma Convolutional Neural Networks (CNN) untuk Pengenalan Wajah. Jurnal Teknologi Informasi (JUTECH), 5(1), 47-54. https://doi.org/10.32546/jutech.v5i1.2584