论文标题
图像压缩和可操作的智能具有深层神经网络
Image Compression and Actionable Intelligence With Deep Neural Networks
论文作者
论文摘要
如果一个单位由于外部因素无法从源头接收智能，我们将其视为处境不利的用户。我们将其归类为在边缘低连接设备上工作的全神贯注单元。这种情况要求我们使用另一种方法来提供智力，尤其是卫星图像信息，尤其是通常。为了解决这个问题，我们建议对减少信息的调查，以从较小的包装中从卫星图像中传递信息。我们研究了四种技术，以帮助减少交付的信息：传统图像压缩，神经网络图像压缩，对象检测图像切口和标题图像。当考虑不利的用户时，这些机制中的每一个都有其优势和权衡。
If a unit cannot receive intelligence from a source due to external factors, we consider them disadvantaged users. We categorize this as a preoccupied unit working on a low connectivity device on the edge. This case requires that we use a different approach to deliver intelligence, particularly satellite imagery information, than normally employed. To address this, we propose a survey of information reduction techniques to deliver the information from a satellite image in a smaller package. We investigate four techniques to aid in the reduction of delivered information: traditional image compression, neural network image compression, object detection image cutout, and image to caption. Each of these mechanisms have their benefits and tradeoffs when considered for a disadvantaged user.
