Abstract
Wireless sensor networks are used in various day-to-day applications. With advanced technology, wireless sensor networks (WSNs) play a key role in networking technologies since it can be expanded without communication infrastructure. There is so much demand for wireless sensor networks that are useful in day-to-day applications. Various techniques like multilayer restricted Boltzmann machine (RBM) network and variational autoencoder (VAE) methods are designed for transmission of images in wireless sensor networks and tested for both gray (2D) and color (3D) images in this paper. The proposed variational autoencoder method is compared with multilayer RBM when the layers are 2, 4, and 8, and the peak signal-to-noise ratio (PSNR) and signal-to-noise ratio (SNR) are compared.
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Aruna Deepthi, S., Sreenivasa Rao, E., Giri Prasad, M.N. (2019). Image Compression in Wireless Sensor Networks Using Autoencoder and RBM Method. In: Saini, H., Singh, R., Kumar, G., Rather, G., Santhi, K. (eds) Innovations in Electronics and Communication Engineering. Lecture Notes in Networks and Systems, vol 65. Springer, Singapore. https://doi.org/10.1007/978-981-13-3765-9_29
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DOI: https://doi.org/10.1007/978-981-13-3765-9_29
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