IWIP History

2021 International Workshop on Image Processing (IWIP 2021)

June 25-27, 2021 丨 Virtual Conference

2021 International Workshop on Image Processing (IWIP 2021) was held during June 25-27, 2021 in Beijing, China.
2021年图像处理国际研讨会(IWIP 2021)已于2021年6月25-27日已线上会议方式成功举办.

Several current and upcoming frontier technologies, innovative solutions, research results, as well as enterprises related to Pattern Recognition and their applications will be presented.  The organizing committee has invited  Prof. Xudong Jiang (IEEE Fellow, Nanyang Technological University, Singapore), Prof. Yiu-ming Cheung (IEEE Fellow, Hong Kong Baptist University, Hong Kong), Prof. Dr. Wenbing Zhao (Cleveland State University, USA), Prof. Tieling Chen (University of South Carolina Aiken, USA) to deliver keynote and Plenary speeches.

在本次会议中, 来自新加坡南洋理工大学的蒋旭东教授报告的题目是"基于深度机器学习的语义场景分割", 由于各种场景图像中物体的形状多样, 布局复杂, 不同物体的上下文空间尺度和形状有很大的变化, 所以判别上下文和聚合多尺度特征以实现场景分割是一项具有挑战性的任务; 来自香港浸会大学的张晓明教授的报告题目为"目标域对偶分解: 一种优化偏微分目标函数的有效方法", 为了解决目标函数的一部分可微而其余部分不可微, 或者目标函数仅在域的一部分中可微的优化问题, 张教授提出了一种基于目标分解和域分解的双重分解的方法; 来自美国克利夫兰州立大学的赵文斌教授的报告题目为"使用Kinect骨架数据进行人员识别", 在使用Kinect骨架数据进行人物识别的现有工作中, 由于Kinect的视野非常有限, 不利于获得周期性特征,而且行走时骨骼的3D位置的测量质量较差, 导致从Kinect骨骼数据中可靠地提取动态步态特征非常困难; 来自美国南卡罗莱纳大学的陈铁林教授的报告题目为"HDI颜色模型下的颜色分布比较", 由于现实生活中的颜色的复杂性, 人类视觉系统的主观感知无法很好的比较色差.

Some authors' presentations are recorded as below:

EXCELLENT ORAL PRESENTATIONS

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Session 1: Digital Image Analysis and Processing
Paper Title: Infraredand Visible Image Fusion Algorithm for Substation Equipment Based on NSCT and Siamese Network
YangYang, China Electric Power Research Institute, China

Session 2: Computer Science and Image Application Technology
Paper Title: Local Instrument with Geo-Tagging for Area Storm Surges (LIGTASS): A Detection and Monitoring System for Marine Vessels
Jessie Balbin, Mapua University, Philippines

Session 3: Computer Science and Data Analysis
Paper Title: Tensor-patch-based Discriminative Marginalized Least Squares Regression for Membranous Nephropathy Hyperspectral Data
Tianhong Chen, Beijing Institute of Technology, China

Session 4: Big Data and Data Engineering
Paper Title: Mobile Geo-tagging and Cloud-based Underwater Garbage Identification using Convolutional Neural Network
Jessie Balbin, Mapua University, Philippines