Demo Abstract: Image Storage and Broadcast over BLE with Deep Neural Network Autoencoding

Chong Shao, S. Nirjon
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引用次数: 2

Abstract

This demo in an implementation of a new Deep Image Beacon system that is capable of broadcasting color images over a very long period (years, as opposed to days or weeks) using a set of cheap, low-power, memory-constrained Bluetooth Low Energy (BLE) beacon devices. We adopt a deep neural network image encoder to encode the given input image and generates a compact representation of the image. The representation can be as short as 10 bytes. On the receiver end, we adopt a deep neural network decoder running on a mobile device. When the mobile device receives the BLE broadcasted image data, it decodes the original image. We develop a pair of smartphone applications. One application takes an image and user-requirements as inputs, shows previews of different quality output images, writes the encoded image into a set of beacons. The second application reads the broadcasted image back.
摘要:基于深度神经网络自编码的BLE图像存储与广播
这个演示是一个新的深度图像信标系统的实现,该系统能够在很长一段时间(几年,而不是几天或几周)内广播彩色图像,使用一组廉价、低功耗、内存受限的蓝牙低功耗(BLE)信标设备。我们采用深度神经网络图像编码器对给定的输入图像进行编码,并生成图像的紧凑表示。该表示可以短至10字节。在接收端,我们采用了运行在移动设备上的深度神经网络解码器。当移动设备接收到BLE广播图像数据时,对原始图像进行解码。我们开发了两个智能手机应用程序。一个应用程序将图像和用户需求作为输入,显示不同质量输出图像的预览,将编码图像写入一组信标。第二个应用程序读取广播的图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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