ECTI TRANSACTIONS ON COMPUTER INFORMATION TECHNOLOGYVolume 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 PDFThe 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...
Deep Learning, Landmark Recognition, Convolutional Neural Networks, NU-LiteNet