应用程序接口(简称 API),又称为应用编程接口,就是软件系统不同组成部分衔接的约定。

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报告题目:

OpenCV 4.x and more new tools for CV R&D

报告简介:

当今的计算机视觉算法大多采用深度学习技术,这种技术既需要计算,又需要数据。现代硬件通常是异构的,并且越来越难以有效地编程。OpenCV 4提供了新的功能来解决这些新的挑战,并为开发人员提供了方便的API来处理复杂性。您可以在一个流行的深度学习框架(Caffe/TensorFlow/Darknet/Torch/ONNX格式兼容框架)中训练神经网络模型,并使用OpenCV运行它,而不依赖于origin框架。本教程涵盖OpenCV 4特性介绍,深度学习模块使用C++中的代码示例、Python、Java和JavaScript(EnScript绑定)。我们还将回顾深网络的不同计算后端,如OpenCL和Intel®推理机。

嘉宾介绍:

Alexander Bovyrin,Nikita Manovich,Sergei Nosov,Dmitry Kurtaev。

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Android utilizes a security mechanism that requires apps to request permission for accessing sensitive user data, e.g., contacts and SMSs, or certain system features, e.g., camera and Internet access. However, Android apps tend to be overprivileged, i.e., they often request more permissions than necessary. This raises the security problem of overprivilege. To alleviate the overprivilege problem, this paper proposes MPDroid, an approach that combines static analysis and collaborative filtering to identify the minimum permissions for an Android app based on its app description and API usage. Given an app, MPDroid first employs collaborative filtering to identify the initial minimum permissions for the app. Then, through static analysis, the final minimum permissions that an app really needs are identified. Finally, it evaluates the overprivilege risk by inspecting the apps extra privileges, i.e., the unnecessary permissions requested by the app. Experiments are conducted on 16,343 popular apps collected from Google Play. The results show that MPDroid outperforms the state-of-the-art approach significantly.

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