A Comparative Analysis of EfficientNet and MobileNet Models’ Performance on Limited Datasets: An Example of American Sign Language Alphabet Detection

Hongwen Pu; Keyi Yi

doi:10.54097/yh5d3s04

Authors

Hongwen Pu
Keyi Yi

DOI:

https://doi.org/10.54097/yh5d3s04

Keywords:

EfficientNet, MobileNet, architecture, sign language, small-scale datasets, combined datasets.

Abstract

This paper explored the performance of EfficientNet architecture and MobileNet architecture while processing sign language alphabets using small-scale datasets. EfficientNet and MobileNet are the two most popular architectures in the computer vision industry. The outbreak of the COVID-19 pandemic demonstrates the importance of investigating two model’s performance while a product needs to be developed in a short time. Previously, research has been conducted on two models, mainly focusing on the two model’s performance while handling small datasets related to medicine. However, there remains a research gap for sign language. A combined dataset obtained from two datasets from Kaggle was used to train the model. The models’ performance under 5 epochs, 10 epochs, and 20 epochs were deduced and compared. In general, the performance of MobileNetV2 models is outstanding, especially under 5 epochs, while other MobileNet and EfficientNet models show an intense overfit. Moving forward, the models could be tested on more powerful platforms and more models could be compared.

Downloads

Download data is not yet available.

References

Tan M, Le Q. Efficientnet: Rethinking model scaling for convolutional neural networks. International conference on machine learning. PMLR, 2019: 6105-6114.

Howard A G, Zhu M, Chen B, et al. Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861, 2017.

Jaryani F, Amiri M. A Pre-Trained Ensemble Model for Breast Cancer Grade Detection Based on Small Datasets. Iranian Journal of Health Sciences, 2023, 11(1): 47-58.

Pramudhita D A, Azzahra F, Arfat I K, et al. Strawberry Plant Diseases Classification Using CNN Based on MobileNetV3-Large and EfficientNet-B0 Architecture. J. Ilm. Tek. Elektro Komput. dan Inform, 2023, 9(3): 522-534.

Yang Y, Zhang L, Du M, et al. A comparative analysis of eleven neural network architectures for small datasets of lung images of COVID-19 patients toward improved clinical decisions. Computers in Biology and Medicine, 2021, 139: 104887.

Kaggle. Kaggle: Your Home for Data Science Kaggle.com. 2022. 2024/1/10. https://www.kaggle.com/.

Akash. ASL Alphabet//www.kaggle.com. 2024/1/10. https://www.kaggle.com/datasets/grassknoted/asl-alphabet.