课程号：EE206000

课程名：遥感与机器学习

英文课程名：Remote Sensing and Machine Learning

开课单位：电子工程学院

授课教师：Gabriel Dauphin

责任教师：全英汇   冯伟

学分/学时：1学分/16学时

教师简介：Gabriel Dauphind的博士和硕士都毕业于法国顶级大学巴黎高科，本科毕业于法国巴黎11大，现在是巴黎十三大的副教授，他的研究方向包括：遥感与分类、深度学习、计算视觉和信号处理。Gabriel Dauphin PHD in Signal Processing (Télécom Paris) 1998-2002Engineering School (Mines ParisTech) Research Degree (University Paris 11) 1993-1998Research directions:Remote Sensing and ClassificatioDeep Learning Based Image CompressionAnalysis and Use of Quality Metrics Inspired by Human Visual System. Application to Image Compression.Gait Recognition with Application to Health Monitoring.Stereoscopic Image Compression Using Combinatorial Optimization.

课程简介：课程主要围绕遥感技术结合机器学习的实际应用。遥感数据在不同的应用研究中，受图像质量、样本质量和模型性能的影响较大，必须结合的多样性技术手段。因此课程首先讲解遥感在环境、土地利用、农业等不同领域中的重要性和应用情况，然后讲解随机森林和深度神经网络等典型的和热门的机器学习方法，最后介绍机器学习在遥感中的实际应用。The course focuses on the practical application of remote sensing technology combined with machine learning. In different application studies of remote sensing data, the received image quality, sample quality, and model performance have a greater impact, and a variety of technical means must be combined. Therefore, the course first explains the importance and application of remote sensing in different fields such as environment, land use, agriculture, etc., then explains typical and popular machine learning methods such as random forests and deep neural networks, and finally introduces the practicality of machine learning in remote sensing. application.

先修课程：无