Biblio

Filters: Author is Li, Hao  [Clear All Filters]
2022-05-06
Fu, Shijian, Tong, Ling, Gong, Xun, Gao, Xinyi, Wang, Peicheng, Gao, Bo, Liu, Yukai, Zhang, Kun, Li, Hao, Zhou, Weilai et al..  2021.  Design of Intermediate Frequency Module of Microwave Radiometer Based on Polyphase Filter Bank. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. :7984–7987.
In this work, an IF(intermediate frequency) module of a hyperspectral microwave radiometer based on a polyphase filter bank (PFB) and Discrete Fourier Transformation (DFT)is introduced. The IF module is designed with an 800MSPS sampling-rate ADC and a Xilinx Virtex-7 FPGA. The module can achieve 512 channels and a bandwidth of 400M and process all the sampled data in real-time. The test results of this module are given and analyzed, such as linearity, accuracy, etc. It can be used in various applications of microwave remote sensing. The system has strong expandability.
2020-06-12
Liu, Junfu, Chen, Keming, Xu, Guangluan, Li, Hao, Yan, Menglong, Diao, Wenhui, Sun, Xian.  2019.  Semi-Supervised Change Detection Based on Graphs with Generative Adversarial Networks. IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. :74—77.

In this paper, we present a semi-supervised remote sensing change detection method based on graph model with Generative Adversarial Networks (GANs). Firstly, the multi-temporal remote sensing change detection problem is converted as a problem of semi-supervised learning on graph where a majority of unlabeled nodes and a few labeled nodes are contained. Then, GANs are adopted to generate samples in a competitive manner and help improve the classification accuracy. Finally, a binary change map is produced by classifying the unlabeled nodes to a certain class with the help of both the labeled nodes and the unlabeled nodes on graph. Experimental results carried on several very high resolution remote sensing image data sets demonstrate the effectiveness of our method.

2017-10-19
Zhang, Peng, Li, Hao, Hu, Chengchen, Hu, Liujia, Xiong, Lei, Wang, Ruilong, Zhang, Yuemei.  2016.  Mind the Gap: Monitoring the Control-Data Plane Consistency in Software Defined Networks. Proceedings of the 12th International on Conference on Emerging Networking EXperiments and Technologies. :19–33.

How to debug large networks is always a challenging task. Software Defined Network (SDN) offers a centralized con- trol platform where operators can statically verify network policies, instead of checking configuration files device-by-device. While such a static verification is useful, it is still not enough: due to data plane faults, packets may not be forwarded according to control plane policies, resulting in network faults at runtime. To address this issue, we present VeriDP, a tool that can continuously monitor what we call control-data plane consistency, defined as the consistency between control plane policies and data plane forwarding behaviors. We prototype VeriDP with small modifications of both hardware and software SDN switches, and show that it can achieve a verification speed of 3 μs per packet, with a false negative rate as low as 0.1%, for the Stanford backbone and Internet2 topologies. In addition, when verification fails, VeriDP can localize faulty switches with a probability as high as 96% for fat tree topologies.