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2nd China Symposium on Cognitive Computing and Hybrid Intelligence, CCHI 2019

作者： Liu, Sen Zhao, Shuxin Pang, Yingxue Chen, Zhibo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781728140919

There is plenty of human-machine joint decision-making scenarios in the real world applications, such as driving assistant, suspect identification, medical diagnosis, etc. Existing algorithms propose that machine should give a rejection option when having a high risk or uncertainty score so that the input can be passed to human to make the decision. This is an interesting algorithmic model of human-machine collaboration, but implicitly assumes that humans are more trustworthy than machines. Such an assumption ignores the bias and inconsistency of human, especially in scenarios where machines have superior recognition ability than humans. In this work, we investigate the human-machine joint decision-making problem in distorted surveillance videos, where machines experimentally prove to be comparable to human beings in tolerance to distortion, sometimes even stronger. We propose a new human-machine joint decision-making framework by considering both the confidences of machine and human. To obtain the confidence of human, we build a real-life human decision-making database and propose a deep neural network to estimate human's confidence. Then, confidence alignment method and decision rule are proposed to further output the final decision. Experiments demonstrate that the proposed framework can make less human intervention and more accurate decisions in several human-machine joint decision-making scenarios. © 2019 IEEE.

关键词： Deep neural networks

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Analysis and Prediction of Vehicle Exhaust Emission Using ANN 36

Analysis and Prediction of Vehicle Exhaust Emission Using AN...

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第36届中国控制会议

作者： Zhenyi Xu Yu Kang Wenjun Lv Department of Automation and State Key Laboratory of Fire Science University of Science and Technology of China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences

ISBN: (纸本)9781538629185

This paper focused on the analysis of vehicle emission based on the Hefei remote sensing data during the last three *** we propose a three-layer artificial neural network model for predicting vehicle exhaust emission using remote sensing ***,we take adaptive-lasso algorithm to analyze the various factors from the emission data,and determine the principal ***,after doing principal components analysis and selecting algorithm and architecture,the Back-Propagation neural network model with 7-12-1 architecture was established as the optimal ***,we give the prediction results on the testing data-set and prove the potentiality and validity of the proposed method in the prediction of vehicle exhaust emission.

关键词： Vehicle Exhaust Emission Adaptive-Lasso Artificial Neural Network

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Hybrid transform for HEVC-based lossless coding

Hybrid transform for HEVC-based lossless coding

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2014 IEEE International Symposium on Circuits and systems, ISCAS 2014

作者： Chen, Fangdong Zhang, Jinlei Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781479934324

The High Efficiency Video Coding (HEVC) with the transform bypass mode is simple but inefficient for lossless coding. For this reason, we propose a novel transform to further eliminate the redundancy between residues of different blocks in intra prediction. Dependent on intra prediction modes, the proposed transform is adaptable to exploit correlations of residues formed by different modes. In order to accurately obtain parameters of the transform matrix, an approach similar to the Wiener filtering method is adopted. Experimental results show that on top of the lossless coding mode in HEVC, our method offers the performance with a 7.4% bit-rate reduction on average for All Intra Main configuration. Compared with other representative algorithms, our proposal still shows an improvement in the compression ratio, without substantial increases of computational complexity in the encoder or decoder. © 2014 IEEE.

关键词： Forecasting

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Robust sketch-based image retrieval by saliency detection 22nd

Robust sketch-based image retrieval by saliency detection

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22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Zhang, Xiao Chen, Xuejin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9783319276700

Sketch-based image retrieval (SBIR) has been extensively studied for decades because sketch is one of the most intuitive ways to describe ideas. However, the large expressional gap between hand-drawn sketches and natural images with small-scale complex structures is the fundamental challenge for SBIR systems. We present a novel framework to efficiently retrieve images with a query sketch based on saliency detection. In order to extract primary contours of the scene and depress textures, a hierarchical saliency map is computed for each image. Object contours are extracted from the saliency map instead of the original natural image. Histograms of oriented gradients (HOG) are extracted at multiple scales on a dense gradient field. Using a bag-of-visual-words representation and an inverted index structure, our system efficiently retrieves images by sketches. The experimental results conducted on a dataset of 15 k photographs demonstrate that our method performs well for a wide range of natural scenes. © Springer International Publishing Switzerland 2016.

关键词： Image retrieval

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Markov Decision Process Based Wireless Multicast Opportunistic Routing 33

Markov Decision Process Based Wireless Multicast Opportunist...

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第三十三届中国控制会议

作者： Ma Dianbo Tan Xiaobin Zhou Zijian Yu Shanjin Department of Automation University of Science and Technology of China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781479947249

There are more and more pervasive applications of Wireless Multicast Network, such as the video conference, the voice transmission and the software updates etc. The traditional wireless multicast routing method is to construct a multicast tree,which may ignore many available links. This paper presents Markov Decision Process Based Multicast Opportunistic Routing Model. Whether each node of the whole network has received a packet stands for different states of a Markov chains. That is to say that Markov state transition is a routing process. This paper provides a new approach for the study of wireless multicast networks routing. In the reward function of the model, the consumption of Request and ACK among the nodes is abundantly considered. In accordance with each state of the network, the network chooses the optimal forwarding nodes which make the reward function of the model maximum. The experiment and the simulation results proves MDP is most effective routing scheme,and meets with the network system's requirement.

关键词： Markov Decision Process,Opportunistic Routing,Multicast,reward function

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MobiNDN:A Mobility Support Architecture for NDN 33

MobiNDN:A Mobility Support Architecture for NDN

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第三十三届中国控制会议

作者： Zhou Zijian Tan Xiaobin Li Hebi Zhao Zhifan Ma Dianbo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Department of Automation University of Science and Technology of China

ISBN: (纸本)9781479947249

Named Data networking(NDN) has emerged as a new communication paradigm designed for efficient dissemination of data. However, mobility issues are not considered sufficiently. Consumer or producer mobility can incur request staleness issue, the loss of Interest and Data packets and communication delay. Through analysis, we consider how to forward the buffered data from old access point(AP) to new one and how to keep routing consistency during handoff stage are two key points to address mobility issue in NDN. To minimize the loss of Interest and Data,handoff delay during moving, we design a mobility support architecture(MobiNDN), which is a centralized system architecture and consists of initialization and three stages:registration,deletion and updating. We design three mobility scenarios and schemes and evaluate the performance of MobiNDN by comparing it against exiting NDN using extensive ndnSIM simulation. Our simulation results clearly show that MobiNDN architecture effectively decreases handoff delay and receives data packets during/after handoffs comparing with the exiting NDN.

关键词： Controller,Mobility Support,NDN

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Improved rate-distortion optimization algorithms for hevc lossless coding 21

Improved rate-distortion optimization algorithms for hevc lo...

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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Chen, Fangdong Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9783319144443

To avoid distortion, the quantization is not implemented on residues for lossless mode in HEVC. As a result, the conventional lambda model in Rate-Distortion Optimization (RDO), where lambda is related to the quantization parameter (QP), is unreasonable for lossless coding. This paper first demonstrates the role that lambda value plays in the rough RDO of HEVC lossless coding, and a Simulated Annealing algorithm based approach is proposed to obtain the most appropriate lambda for each largest coding unit. Considering the computational complexity, the other simplified method using least square errors prediction is proposed to improve the rough RDO process. Experimental results reveal that on top of the lossless coding mode, the improved method offers the performance with a 1.0%, 1.3% and 1.1% bit-rate reduction on average for Random-access Main, Low-delay B Main and Low-delay P Main configurations, respectively, while brings negligible increases of computational complexity in the encoder. © Springer International Publishing Switzerland 2015.

关键词： Computational complexity

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ERROR ESTIMATION and UNAMBIGUOUS RECONSTRUCTION for Chinese FIRST DUAL-CHANNEL SPACEBORNE SAR IMAGING

ERROR ESTIMATION and UNAMBIGUOUS RECONSTRUCTION for Chinese ...

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ISPRS geospatial Week 2017

作者： Jin, T. Qiu, X. Hu, D. Ding, C. University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Technology in Geospatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) faced with conventional SAR. Error estimation and unambiguous reconstruction are two crucial techniques for obtaining high-quality imagery. This paper demonstrates the experimental results of the two techniques for Chinese first dualchannel spaceborne SAR imaging. The model of Chinese Gaofen-3 dual-channel mode is established and the mechanism of channel mismatches is first discussed. Particularly, we propose a digital beamforming (DBF) process composed of the subspace-based error estimation algorithm and the reconstruction algorithm before imaging. The results exhibit the effective suppression of azimuth ambiguities with the proposed DBF process, and indicate the feasibility of this technique for future HRWS SAR systems. © Authors 2017.

关键词： digital beamforming (DBF) high-resolution and wide-swath (HRWS) orthogonal subspace method (OSM) Synthetic aperture radar (SAR) unambiguous reconstruction

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Unsupervised classification of polarimetric circular SAR images based on H/α/Multi-aperture polarimetric entropy 12

Unsupervised classification of polarimetric circular SAR ima...

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12th European Conference on Synthetic Aperture Radar, EUSAR 2018

作者： Hong, Wen Xue, Feiteng Lin, Yun Chen, Shiqiang Shen, Wenjie University of Chinese Academy of Sciences Beijing China Institute of Electronics Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geospatial Information Processing and Application System Beijing China

ISBN: (纸本)9783800746361

In conventional polarimetric synthetic aperture radar(PolSAR), targets are usually assumed isotropic and potential polarimetric variations across azimuth are unconsidered. As to circular SAR (CSAR), the azimuthal view angle is much larger. Polarimetric variations across azimuth are no longer negligible. H/α unsupervised classification method classifies data by polarimetric properties. H/α method can not distinguish anisotropic and isotropic targets which have same polarimetric properties when applied to polarimetric CSAR(Pol-CSAR) data. Recently multi-aperture polarimetric entropy(MAPE) was proposed in Ref. [10]. MAPE can be used to identify anisotropic and isotropic targets. In this paper, an unsupervised classification method based on H/α/MAPE is proposed. The proposed classification method classifies data with H/α/MAPE space. Anisotropic and isotropic targets which have same polarimetric properties are well classified into two classes by H/α/MAPE method. The effectiveness and advantages of H/α/MAPE method are demonstrated on Pol-CSAR data, acquired from the Institute of Electronics airborne CSAR system at P-band. © VDE VERLAG GMBH Â Berlin Â Offenbach.

关键词： Synthetic aperture radar

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HPHR-SAR-Net: Hyperpixel High-Resolution SAR Imaging Network Based on Nonlocal Total Variation

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2023年 16卷 8595-8608页

作者： Zhou, Guoru Xu, Zhongqiu Fan, Yizhe Zhang, Zhe Qiu, Xiaolan Zhang, Bingchen Fu, Kun Wu, Yirong Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing100045 China University of Chinese Academy of Sciences Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100045 China Suzhou Aerospace Information Research Institute Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Suzhou215009 China

High resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. First, these algorithms tend to focus on local information, neglecting nonlocal information between different pixel patches. Second, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Third, the process of high-resolution SAR imaging generally involves high time and computational complexity, making real-time imaging difficult to achieve. To address these issues, we propose a hyperpixel high-resolution SAR imaging network (HPHR-SAR-Net) for rapid despeckling in high-resolution modes. Based on the concept of hyperpixel techniques, we initially combine nonconvex and nonlocal total variation as compound regularization. This approach more effectively despeckles and manages the relationship between pixels while reducing bias effects caused by convex constraints. Subsequently, we solve the compound regularization model using the alternating direction method of multipliers (ADMM) algorithm and unfold it into a deep unfolding network (DUN). The network's parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the proposed HPHR-SAR-Net is compatible with high-resolution imaging modes, such as spotlight, staring spotlight, and sliding spotlight. In this article, we demonstrate the superiority of HPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that HPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results. © 2008-2012 IEEE.

关键词： Radar imaging

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