Deep Learning Frameworks Evaluation for Image Classification on Resource Constrained Device

 #deeplearning #deeplearningalgorithms #images #imageclassification

Deep Learning Frameworks Evaluation for Image Classification on Resource Constrained Device


Mathieu Febvay and Ahmed Bounekkar, Université de Lyon, France


Each new generation of smartphone gains capabilities that increase performance and power efficiency allowing us to use them for increasingly complex calculations such as Deep Learning. This paper implemented four Android deep learning inference frameworks (TFLite, MNN, NCNN and PyTorch) to evaluate the most recent generation of System On a Chip (SoC) Samsung Exynos 2100, Qualcomm Snapdragon 865+ and 865. Our work focused on image classification task using five state-of-the-art models.


https://www.youtube.com/watch?v=kr-gGh6y8RY&t=2s&ab_channel=ComputerScience%26ITConferenceProceedings

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