Automatic Machine Learning with Imperfect Data for Video Analysis

该项目旨在提出新的算法和技术，以构建一个高效的视频分析系统，这将与澳大利亚的科学和研究优先事项保持一致。具体而言，在本项目中，将提出一种新的基于自动机器学习的网络结构搜索方法，开发一种无监督的域自适应算法，并构建一种生成式数据增强方法。所有这些都将构建一个稳定高效的深度神经网络，它能够高效地处理从真实的场景中捕获的大尺寸视频。医疗保健服务和网络安全等各个领域将从该项目中受益匪浅。

This project aims to propose new algorithms and technologies for constructing an efficient video analysis system, which will be aligned with Australia’s science and research priorities. Specifically, during this project, a novel network structure search method based on auto machine learning will be proposed, an unsupervised domain adaptation algorithm will be developed, and a generative data augmentation method will be constructed. All of these will construct a stable and efficient deep neural network, which is able to process large size videos captured from real scenarios in high efficiencies. Various fields, such as health care service and cybersecurity, will benefit hugely from this project.