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arXiv 2019年

作者： Li, Yu Tang, Sheng Zhang, Rui Zhang, Yongdong Li, Jintao Yan, Shuicheng Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China AI Institute Qihoo 360 Beijing100025 China Department of Electronics and Computer Engineering National University of Singapore Singapore

Unpaired image-to-image translation problem aims to model the mapping from one domain to another with unpaired training data. Current works like the well-acknowledged Cycle GAN provide a general solution for any two domains through modeling injective mappings with a symmetric structure. While in situations where two domains are asymmetric in complexity, i.e. the amount of information between two domains is different, these approaches pose problems of poor generation quality, mapping ambiguity, and model sensitivity. To address these issues, we propose Asymmetric GAN (AsymGAN) to adapt the asymmetric domains by introducing an auxiliary variable (aux) to learn the extra information for transferring from the information-poor domain to the information-rich domain, which improves the performance of state-of-the-art approaches in the following ways. First, aux better balances the information between two domains which benefits the quality of generation. Second, the imbalance of information commonly leads to mapping ambiguity, where we are able to model one-to-many mappings by tuning aux, and furthermore, our aux is controllable. Third, the training of Cycle GAN can easily make the generator pair sensitive to small disturbances and variations while our model decouples the ill-conditioned relevance of generators by injecting aux during training. We verify the effectiveness of our proposed method both qualitatively and quantitatively on asymmetric situation, label-photo task, on Cityscapes and Helen datasets, and show many applications of asymmetric image translations. In conclusion, our AsymGAN provides a better solution for unpaired image-to-image translation in asymmetric domains. Copyright © 2019, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A Method of Searching for Optimal Coalition Structure for Solving Resource Scheduling Problem of Overall Load Balancing in Edge Computing Environments

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Journal of Physics: Conference Series 2020年第3期1550卷

作者： Hu Yanan Li Chunsheng Zhang Kejia School of Computer & Information Technology Northeast Petroleum University Daqing 163318 (PR China) Heilongjiang Provincial Key Laboratory of Oil Big data & Intelligent Analysis Daqing 163318 (PR China)

The cooperative computing resource scheduling problem in the distributed computing environment is usually transformed into the problem about how to find the optimal coalition structure. However, affected by factors such as high node density and large number of concurrent tasks in edge computing environments, it is difficult to formulate resource scheduling schemes for overall load balancing in a large strategic space by traditional methods. In order to solve this problem, we proposed a method of searching for optimal coalition structure based on discrete particle swarm optimization (DPSO). Firstly, we converted the resource scheduling problem of edge computing into an optimization problem model, constructed a new structure of coalition structure to express the resource scheduling scheme, and gave key elements such as optimization objectives, decision variables, and constraint conditions. Secondly, we improved DPSO and designed M-ary discrete particle swarm optimization (MDPSO): improved particle state determination method for adapting to the new expression of the coalition structure, and proposed a power series-based inertia weight computing method to improve the optimization speed and the optimal solution quality. Finally, we simulated real application scenarios and designed comparative experiments on the optimization speed, the optimal solution quality, stability, etc., which verifies that the method proposed in this paper has obvious advantages in solving the resource scheduling problem of overall load balancing in edge computing.

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Optimal seam line detection in laplacian pyramid domain for image stitching

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Journal of computers (Taiwan) 2018年第1期29卷 209-219页

作者： Yan, Wu-Xia Liu, Chuan-Cai Hu, Jun School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

Parallax handing is a challenging problem for image stitching. Optimal seam line method is employed in this paper to deal with the misalignment on panoramas caused by parallax problem. It's an important method for orthoimage stitching in remote sensing. However, failures occur when it used in common image stitching due to the parallax problem. In order to obtain a better panorama for common image, the proposed approach mainly employs optimal seam line and contains the following three steps. First, the parallax problem can be alleviated by geometric correction. Then, the optimal seam line is detected within the overlapping region by dynamic programming in Laplacian pyramid domain. And images were blended by using blending trick on each corresponding level of the pyramids. Finally, the convincing panorama can be obtained by reconstructing the panoramic pyramid. The experiments demonstrated that the proposed method can obtain the clear and seamless panoramas. © 2018 computer Society of the Republic of China. All rights reserved.

关键词： Remote sensing

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Opinion target extraction for the Chinese formal text based on dependency relations 1st

Opinion target extraction for the Chinese formal text based ...

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1st International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2017

作者： Yang, Xiao-Yan Xu, Ge Zhang, Fu-Quan Liao, Xiang-Wen Xu, Lin Department of Computer Science Minjiang University FuzhouFujian350121 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control FuzhouFujian350121 China School of Software Beijing Institute of Technology Beijing10081 China College of Mathematics and Computer Science Fuzhou University FuzhouFujian350108 China Innovative Information Industry Research Institute Fujian Normal University FuzhouFujian350300 China

ISBN: (纸本)9783319707297

Due to the increasing amount of opinion data on the internet, opinion mining has become a hot topic, in which extracting opinion targets is a key step. The state-of-the-art approaches only use direct dependency relation patterns to extract opinion targets and the indirect dependency relation patterns have not been used. In this paper, the dependency relations between opinion target and opinion word are defined, and direct and indirect dependency relation patterns are designed. Then, a bootstrapping approach is used to extract and evaluate both candidate patterns and opinion targets. The experimental results show that in formal text, the approach improves the performance compared with the state-of-the-art approaches for opinion target extraction. © Springer International Publishing AG 2018.

关键词： Sentiment analysis

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Future Development Trend of Multimedia Network 2

Future Development Trend of Multimedia Network

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2018 2nd Annual International Conference on Cloud technology and Communication Engineering, CTCE 2018

作者： Huang, Li Zhang, Kai Hu, Wei Li, Chengcheng College of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan Hubei430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan Hubei430081 China

With the rapid development of computer network, multimedia technology has gradually spread throughout all aspects of people's life. This article, based on the concept and characteristics of multimedia, expounds the application of multimedia technology and the trend of future development. It makes a heavy analysis of multimedia teaching and analyses the meaning and advantage of multimedia teaching. © Published under licence by IOP Publishing Ltd.

关键词： Multimedia systems

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An Iterative Detection/Decoding Algorithm of Correlated Sources for the LDPC-Based Relay Systems

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China Communications 2017年第9期14卷 190-198页

作者： Haiqiang Chen Hang Cao Xiangcheng Li Youming Sun Haibin Wan Tuanfa Qin The School of Computer and Electronic Information Guangxi University Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi University Guangxi Colleges and Universities Key Laboratory of Multimedia Communications and Information Processing Guangxi University

An iterative detection/decoding algorithm of correlated sources for the LDPC-based relay systems is presented. The signal from the source-destination(S-D) link is formulated as a highly correlated counterpart from the relay-destination(R-D) link. A special XOR vector is defined using the correlated hard decision information blocks from two decoders and the extrinsic information exchanged between the two decoders is derived by the log-likelihood ratio(LLR) associated with the XOR vector. Such the decoding scheme is different from the traditional turbo-like detection/decoding algorithm, where the extrinsic information is computed by the side information and the soft decoder outputs. Simulations show that the presented algorithm has a slightly better performance than the traditional turbo-like algorithm(Taking the(255,175) EG-LDPC code as an example, it achieves about 0.1 dB performance gains aroundBLER=10^(-4)). Furthermore, the presented algorithm requires fewer computing operations per iteration and has faster convergence rate. For example, the average iteration of the presented algorithm is 33 at SNR=1.8 dB, which is about twice faster than that of the turbo-like algorithm, when decoding the(961,721) QC-LDPC code. Therefore, the presented decoding algorithm of correlated sources provides an alternative decoding solution for the LDPC-based relay systems.

关键词： correlated sources iterative de-coding LDPC codes relay channel

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Harmony-Search and Otsu based System for Coronavirus Disease (COVID-19) Detection using Lung CT Scan Images

arXiv

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arXiv 2020年

作者： Rajinikanth, V. Dey, Nilanjan Raj, Alex Noel Joseph Hassanien, Aboul Ella Santosh, K.C. Raja, N. Sri Madhava Department of Electronics and Instrumentation Engineering St. Joseph’s College of Engineering Chennai600119 India Department of Information Technology Techno India College of Technology KolkataWest Bengal700156 India Key Laboratory of Digital Signal and Image Processing of Guangdong Province Department of Electronic Engineering College of Engineering Shantou University Shantou Guangdong China Faculty of Computers and Artificial Intelligence Cairo University Egypt Department of Computer Science University of South Dakota 414 E Clark St VermillionSD57069 United States

Pneumonia is one of the foremost lung diseases and untreated pneumonia will lead to serious threats for all age groups. The proposed work aims to extract and evaluate the Coronavirus disease (COVID-19) caused pneumonia infection in lung using CT scans. We propose an image-assisted system to extract COVID-19 infected sections from lung CT scans (coronal view). It includes following steps: (i) Threshold filter to extract the lung region by eliminating possible artifacts;(ii) Image enhancement using Harmony-Search-Optimization and Otsu thresholding;(iii) Image segmentation to extract infected region(s);and (iv) Region-of-interest (ROI) extraction (features) from binary image to compute level of severity. The features that are extracted from ROI are then employed to identify the pixel ratio between the lung and infection sections to identify infection level of severity. The primary objective of the tool is to assist the pulmonologist not only to detect but also to help plan treatment process. As a consequence, for mass screening processing, it will help prevent diagnostic burden. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

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A Network Pruning Method for Remote Sensing Image Scene Classification

A Network Pruning Method for Remote Sensing Image Scene Clas...

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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Baogui Qi He Chen Yin Zhuang Shaorong Liu Liang Chen Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China School of Electronic Engineering and Computer Science Peking University Beijing China Beijing Institute of Spacecraft System Engineering Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Deep convolutional neural networks have been widely used to improve remote sensing image scene classification performance. However, most of these networks include many parameters and need many computational resources. Which hinders the applications of these networks when facing the satellite, plane or other mobile platforms. In this paper, we introduce a network pruning framework which can reduce the size of the network model and maintain the classification accuracy. In this framework, we train the pruned model using both the original unpruned model's output and training dataset. Which can learn more information than retrain using dataset only. In our experiments, we evaluate our method for remote sensing scene classification on NWPU-RESISC45 dataset. The results demonstrate that our method was effective and maintained the model classification accuracy.

关键词： pruning convolutional neural networks scene classification compression deep learning

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Learning Robust Facial Landmark Detection via Hierarchical Structured Ensemble

Learning Robust Facial Landmark Detection via Hierarchical S...

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International Conference on computer Vision (ICCV)

作者： Xu Zou Sheng Zhong Luxin Yan Xiangyun Zhao Jiahuan Zhou Ying Wu College of Life Science and Technology Huazhong University of Science & Technology (HUST) Wuhan China National Key Laboratory of Science & Technology on Multi-Spectral Information Processing HUST Wuhan China School of Aritificial Intelligence and Automation HUST Wuhan China Department of Electrical and Computer Engineering Northwestern University IL USA

ISBN: (数字)9781728148038

ISBN: (纸本)9781728148045

Heatmap regression-based models have significantly advanced the progress of facial landmark detection. However, the lack of structural constraints always generates inaccurate heatmaps resulting in poor landmark detection performance. While hierarchical structure modeling methods have been proposed to tackle this issue, they all heavily rely on manually designed tree structures. The designed hierarchical structure is likely to be completely corrupted due to the missing or inaccurate prediction of landmarks. To the best of our knowledge, in the context of deep learning, no work before has investigated how to automatically model proper structures for facial landmarks, by discovering their inherent relations. In this paper, we propose a novel Hierarchical Structured Landmark Ensemble (HSLE) model for learning robust facial landmark detection, by using it as the structural constraints. Different from existing approaches of manually designing structures, our proposed HSLE model is constructed automatically via discovering the most robust patterns so HSLE has the ability to robustly depict both local and holistic landmark structures simultaneously. Our proposed HSLE can be readily plugged into any existing facial landmark detection baselines for further performance improvement. Extensive experimental results demonstrate our approach significantly outperforms the baseline by a large margin to achieve a state-of-the-art performance.

关键词： Robustness Heating systems Detectors Face Shape Mathematical model

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A big data enabled channel model for 5G wireless communication systems

arXiv

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arXiv 2020年

作者： Huang, Jie Wang, Cheng-Xiang Bai, Lu Sun, Jian Yang, Yang Li, Jie Tirkkonen, Olav Zhou, Ming-Tuo National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China School of Cyber Science and Technology Beihang University Beijing100191 China Shandong Provincial Key Lab of Wireless Communication Technologies School of Information Science and Engineering Shandong University Qingdao266237 China ShanghaiTech University Shanghai201210 China Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai200240 China Aalto University Espoo02150 Finland Shanghai200050 China

The standardization process of the fifth generation (5G) wireless communications has recently been accelerated and the first commercial 5G services would be provided as early as in 2018. The increasing of enormous smartphones, new complex scenarios, large frequency bands, massive antenna elements, and dense small cells will generate big datasets and bring 5G communications to the era of big data. This paper investigates various applications of big data analytics, especially machine learning algorithms in wireless communications and channel modeling. We propose a big data and machine learning enabled wireless channel model framework. The proposed channel model is based on artificial neural networks (ANNs), including feed-forward neural network (FNN) and radial basis function neural network (RBF-NN). The input parameters are transmitter (Tx) and receiver (Rx) coordinates, Tx-Rx distance, and carrier frequency, while the output parameters are channel statistical properties, including the received power, root mean square (RMS) delay spread (DS), and RMS angle spreads (ASs). Datasets used to train and test the ANNs are collected from both real channel measurements and a geometry based stochastic model (GBSM). Simulation results show good performance and indicate that machine learning algorithms can be powerful analytical tools for future measurement-based wireless channel modeling. Copyright © 2020, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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