Face Identification System Using Convolutional Neural Network for Low Resolution Image

Arafah, Muhammad; Achmad, Andani; Indrabayu, -; Areni, Intan Sari

doi:10.1109/comnetsat50391.2020.9328967

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…The results are shown in Table 11. al, 2022;Taherkhani et al, 2019;Guo et al, 2017;Qin et al, 2019;Filippidou and Papakostas, 2020;Perti et al, 2020;Sepas-Moghaddam et al, 2020;Zhiqi, 2021;Tran et al, 2022;Luttrell et al, 2017;Nam et al, 2018;Chandran et al, 2018;Choi and Lee, 2020;Zangeneh et al, 2020;Kim et al, 2020) ResNet (He et al, 2016) (Ling et al, 2020;Li et al, 2022;Horng et al, 2022;Li et al, 2022;Kim et al, 2020;Feng et al, 2020;Arafah et al, 2020;Almabdy and Elrefaei, 2019;Setio Aji et al, 2022;Gruber et al, 2017;Hou et al, 2020;Filippidou and Papakostas, 2020;Alkanhal et al, 2023;Zhou et al, 2020) AlexNet (Krizhevsky et al, 2012) (Bukovčiková et al, 2017;Bussey et al, 2017;Liu et al, 2017;Khan et al, 2019b;Han, 2021;H et al, 2023;Almabdy and Elrefaei, 2019;Ma et al, 2018;Alhan...…”

Section: Assessment Of Q3: What Type Of Cnn Model Is Most Commonly Us...mentioning

confidence: 99%

“…It is important to notice that the second most largest category goes to private datasets with 34 papers (Zhou et al, 2018;Ara et al, 2017;Phankokkruad, 2018;Gilani and Mian, 2018;Khan et al, 2019b;Qin et al, 2019;Liu et al, 2019;Peng et al, 2019;Mangal et al, 2020;Lv et al, 2020;Perti et al, 2020;Kim et al, 2017;Irjanto and Surantha, 2020;Arafah et al, 2020;Prasetyo et al, 2021;Moon et al, 2017;Chandran et al, 2018;Yang et al, 2018;Son et al, 2020;Alhanaee et al, 2021;Khan et al, 2020;Nakajima et al, 2021;Talahua et al, 2021;He and Ding, 2023;Karlupia et al, 2023;Bussey et al, 2017;Li et al, 2022;Filippidou and Papakostas, 2020;Bussey et al, 2017;Singh et al, 2022;Setio Aji et al, 2022;Wang et al, 2022;Lestari et al, 2021) creating their own datasets for testing. There are advantages and disadvantages to developing and utilizing private face image datasets for CNN-based face recognition.…”

Section: Assessment Of Q3: What Type Of Cnn Model Is Most Commonly Us...mentioning

confidence: 99%

“…(Yang et al, 2020) propose an enhanced model of face recognition which is based on a Multi-task CNN and integrated application of FaceNet and LBP method. (Arafah et al, 2020) determine the performance of face identification on closed circuit television (CCTV) cameras. They use ResNet50 architecture, ArcFace as a loss function, and Cosine Similarity for the face identification process.…”

Section: 60%mentioning

confidence: 99%

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Convolutional Neural Networks for Face Recognition: A Systematic Literature Review

Barcic¹,

Grd²,

Tomičić³

2023

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This paper presents a comprehensive overview of Convolutional Neural Networks (CNNs) in the context of face recognition. By analyzing 150 research papers, we investigate major publication channels, temporal trends, prevalent CNN models, primary data sets, accuracy levels, primary research focuses, and future prospects for improving CNN-based facial recognition. A major focus is placed on identifying prevalent CNN architectures, techniques used for facial recognition and shedding light on the evolving landscape of CNN designs. Furthermore, we examine the datasets used for training and testing CNNs, and evaluate the accuracy levels achieved by these models. Lastly, we discuss future directions for enhancing CNN-based facial recognition, including addressing bias and fairness, improving robustness to environmental variations, privacy preservation, and exploring transfer learning and multimodal fusion. This paper serves as a valuable resource, summarizing major trends in CNN-based face recognition. It provides insights for researchers and practitioners, guiding future advancements in this rapidly evolving field.

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