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Haobo Lv NO.17 Xinxi Road New Industrial Park Xi'an Hi-Tech Industrial Development Zone Xi'an,Shaanxi,P.R.China Xi'an Institute of Optics and Precision Mechanics of CAS lhbzwd_@_gmail.com |
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I am a 2nd year postgraduate student in the Center for OPTical IMagery Analysis and Learning (OPTIMAL), Chinese Academy of Sciences. My advisor is Prof. Yuan Yuan. I am interested in Remote Sensing, GIS, and Machine Learning. Education
Research
Interests
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Remote Sensing:
Dimensionality reduction, Change Detection, Atmospheric Remote Sensing ~~
Computer Vision:
Visual Odometry, 3D scene parsing ~~
Machine Learning:
Dimensionality Reduction, Semi-supervised Learning, Metric Learing ~~
2D & 3D scene parsing and
its applications. Research
Experience
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Research
Project (2010.10-2012.4), Innovative Experiment of National Undergraduate Project of Wuhan University, Wuhan. Mentor: [Liangming Liu], Juan Du, . Project: Water Quality Monitoring of Liangzi Lake. Developed a system
that uses HJ-1A/B staellite to monitor the quality of Liangzi Lake in Hubei.
Data-dependent Semi-supervised Hyperspectral Image Classification This paper proposed a Data-dependent semi-supervised (DDSS) method for hyperspectral image classification.
This paper extends DDSS by considering unlabeled data to prove that the unlabeled data is helpful for DR,
and the proposed can obtained a better performance.. A Semi-supervised Euclidean Embedding
Dimensionality Reduction Method for
Hyperspectral Image This article proposes an approach to reduce the dimension of multivariate data, where a core contribution lies on the formality of including “unlabeled” samples in the proposed semi-supervised model for the task of data dimension reduction (DDR). Specifically, the approach employs Euclidean embedding for DDR and SVM to measure performance accuracy.. Semi-supervised Change Detection Method for Multi-temporal Hyperspectral Image This project investigates novel metric learning methods to
detect the landcover change information of multi-temporal hyperspectral imagery. We have developed efficient
optimization methods for study the change areas, as well as learning
methods for learning metric matrix. It was applied to
three real hyperpsectral image applications and received good performance. Water Quality Monitoring of Liangzi Lake by HJ-1A/B CCD Data Innovative Experiment of National Undergraduate Project of Wuhan University,
Wuhan. Developed a system that utilizes HJ-1A/B satellite to monitor the quality of Liangzi
Lake in Hubei. Haobo Lv,
Y. Yuan, and L. xiaoqiang. Data-dependent Semi-supervised Hyperspectral Image Classification.
In IEEE China Summit and International Conference on Signal and Information Processing .
(ChinaSIP), 2013. [PDF]
D. Juan,
Haobo Lv, Z. Yawen,
L. Xiaojun,and Z. Xiang,. The water quality dynamic monitoring research
based on HJ-1A/B CCD Data.
The high resolution remote sensing data processing and application of workshop,
((ISTP)), 2012. |
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