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直播回放 Hyperspectral Imaging: Seeing and Understanding the World beyond the Visible Spectrum 高光谱成像:从可见光谱之外观察和理解世界
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1. Topic: Hyperspectral Imaging: Seeing and Understanding the World beyond the Visible Spectrum

演讲题目:高光谱成像:从可见光谱之外观察和理解世界


2. Language: English

语言:英文


3. Speaker: Jun Zhou received his PhD degree in Computing Science from the University of Alberta in 2006. He joined the School of Information and Communication Technology at Griffith University in 2012, where he is now an Associate Professor.  He is the Deputy Director of the ARC Research Hub for Driving Farming Productivity and Disease Prevention, funded for over 10 million Australian dollars from 2019 to 2024. Dr Zhou was a winner of the Discovery Early Career Research Award from the Australian Research Council. His research interests are pattern recognition, computer vision, hyperspectral imaging and their applications to remote sensing, agriculture, environment and health. 

告人周峻,2006年获阿尔伯塔大学计算机科学博士学位,2012年加入格里菲斯大学信息与通信技术学院,现为该学院副教授。他是澳大利亚研究理事会(ARC)提高农业生产率和疾病预防研究中心(Driving Farming Productivity and Disease Prevention)副主任,该中心从2019年到2024年的科研基金超过1000万澳元。周博士曾获得ARC“发现早期职业研究奖”。主要研究领域为模式识别、高光谱图像处理、计算机视觉及其在遥感、环境、农业和医疗中的应用。


4. AbstractHyperspectral imagery contains rich spectral and spatial information on object materials in a scene. It provides a means to see and understand the world beyond the visible spectrum.  Traditional hyperspectral image processing methods mainly focus on pixel-level spectral analysis. On the contrary, computer vision covers color, texture, and various spatial and structural features of objects, but not spectral information. This talk introduces the latest efforts in bridging the gap between spectral and spatial domains to enable more effective image analysis. It also gives an overview of hyperspectral imaging technology and its real-world applications. 
报告摘要高光谱图像包含丰富的空间信息和光谱信息。它让我们能够从可见光谱之外观察和理解世界。传统的高光谱图像处理方法主要集中在像素级的光谱分析。相反,计算机视觉涵盖了物体的颜色、纹理以及各种空间和结构特征,而不仅仅是光谱信息。本报告将介绍在弥合光谱和空间领域之间的差距以便更有效地进行图像分析方面的最新进展以及概述高光谱成像技术及其实际应用。

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