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EXPERIMENTAL COMPARISON OF CONVOLUTION NEURON NETWORK ARCHITECTURES

Ilmārs Apeināns, Vitālijs Žukovs, Sergejs Kodors, Imants Zarembo

Abstract


In this work, authors experimentally compare latencies of convolution neuron network architectures. Authors measured only recognition time. Four architectures were applied in the experiment: AlexNet, AlexNet Separated, MobileNetV1 and MobileNetV2. Models were trained using Fruits360 dataset. The Android mobile application was developed to measure latency on mobile devices. The smallest latency authors obtained using AlexNet Separable model, but the smallest size was provided by MobileNetV2.

Keywords


CNN; Convolution Neuron Network; Model; Tensorflow

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References


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DOI: https://doi.org/10.17770/het2020.24.6742

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