ECTI TRANSACTIONS ON COMPUTER INFORMATION TECHNOLOGY

Volume 13, No. 01, Month MAY, Year 2019, Pages 21 - 28

Nu-litenet: mobile landmark recognition using convolutional neural networks

Chakkrit Termritthikun, Paisarn Muneesawang

Abstract Download PDF

The growth of high-performance mobile devices has resulted in more research into on-device image recognition. The research problems have been the latency and accuracy of automatic recognition, which remain as obstacles to its real-world usage. Although the recently developed deep neural networks can achieve accuracy comparable to that of a human user, some of them are still too slow. This paper describes the development of the architecture of a new convolutional neural network model, NU-LiteNet. For this, SqueezeNet was developed to reduce the model size to a degree suitable for smartphones. The model size of NU-LiteNet was therefore 2.6 times smaller than that of SqueezeNet.Etc...

Keywords

Deep Learning, Landmark Recognition, Convolutional Neural Networks, NU-LiteNet

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