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Systems and methods that leverage deep learning to selectively store images at a mobile image capture device

机译:利用深度学习在移动图像捕获设备上选择性存储图像的系统和方法

摘要

The present disclosure provides an image capture, curation, and editing system that includes a resource-efficient mobile image capture device that continuously captures images. The mobile image capture device is operable to input an image into at least one neural network and to receive at least one descriptor of the desirability of a scene depicted by the image as an output of the at least one neural network. The mobile image capture device is operable to determine, based at least in part on the at least one descriptor of the desirability of the scene of the image, whether to store a second copy of such image in a non-volatile memory of the mobile image capture device or to discard a first copy of such image from a temporary image buffer without storing the second copy of such image in the non-volatile memory.
机译:本公开提供了一种图像捕获,策展和编辑系统,该系统包括连续捕获图像的资源有效的移动图像捕获设备。所述移动图像捕获设备可操作以将图像输入到至少一个神经网络中,并接收由所述图像描绘的场景的期望性的至少一个描述符作为所述至少一个神经网络的输出。移动图像捕获设备可操作来至少部分地基于图像场景的可取性的至少一个描述符来确定是否将这种图像的第二副本存储在移动图像的非易失性存储器中。捕获设备或从临时图像缓冲区中丢弃此类图像的第一副本,而不将此类图像的第二副本存储在非易失性存储器中。

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