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International Conference on Intelligent System and Knowledge Engineering, ISKE

作者： Zhicheng Zhu Chunying Zhang Fengchun Liu College of Science North China University of Science and Technology Mathematical Modeling Innovation Lab North China University of Science and Technology Tangshan China College of Science North China University of Science and Technology Key Laboratory of data Science and Application in Hebei Province Tangshan China College of Science North China University of Science and Technology Tangshan China

ISBN: (数字)9781728123486

ISBN: (纸本)9781728123493

In view of the issue that the writer fills in the information the given complex table, but the author may not be correctly identified as the writer for various reasons. In order to solve this, a text-independent writer recognition model is established in terms of automatic handwriting feature extraction from deep learning MobileNet. The automatic handwriting feature extraction based on MobileNet and the text-independent writer recognition model. Firstly, this paper is preprocessed by using different methods, in order to minimize background information and remain handwriting features to the full extent. Such preprocessing methods include the median filter, binarization, background subtraction, text detection, text segmentation, and image scaling. Then completing recognition by using MobileNet automatic handwriting feature extraction. It can effectively reduce human involvement and enhance the accuracy of recognition. Finally, comparing the established model with traditional classification algorithm and ensemble learning algorithm by experiments. The results show that the model obtained recognition accuracy of 91% or more in the manually collected data set and public data set HCL2000.

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IEEE Global Communications Conference

作者： Jun Tao Xiaoyan Li Jinghao Li Qian Fang Zuyan Wang Fei Tong Key Lab of CNII Southeast University MOE Nanjing China School of Cyber Science and Engineering Southeast University Nanjing China Key Lab of Computer Network Technology of Jiangsu Province Southeast University Nanjing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

With the rapid growth in multimedia information, problems on how to discover the individual interests of users and recommend them with the proper goods have become increasingly difficult. Traditional recommendation algorithms simply utilize user rating logs for recommendations, but ignore lots of useful information which can be expressed as a Heterogeneous Information network. In this paper, we propose a similarity measure, PW-PathSim, to calculate the relevance between two entities of the semi-symmetric weighted meta paths. Then a similarity regularization based recommendation algorithm is proposed to integrate the similarity of users and items with matrix factorization for recommendations. Furthermore, we compare the PW-MFP algorithm with several benchmarks including FunkSVD, HeteFM and DSR. Experimental results with Douban dataset show that it outperforms other HIN-based algorithms in terms of recommendation accuracy.

关键词： Semantics Matrix decomposition Weight measurement Prediction algorithms Motion pictures Collaboration Symmetric matrices

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Revealing the processing history of pitch-shifted voice using CNNs 10

Revealing the processing history of pitch-shifted voice usin...

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10th IEEE International Workshop on Information Forensics and Security, WIFS 2018

作者： Wang, Lihua Liang, Huixin Lin, Xiaodan Kang, Xiangui Guangdong Key Lab of Information Security Technology School of Data and Computer Science Sun Yat-sen University Guangzhou510006 China

ISBN: (纸本)9781538665367

With the emergence of varieties of audio editing software, disguised voices can be generated easily and are able to spoof the automatic speaker verification system. In this work, we focus on the spoofed voice disguised by pitch shifting which is commonly used by popular audio editing software and design a forensic chain to reveal the processing history of pitch-shifted voice signals blindly based on convolutional neural networks (CNNs). Because tracing the disguising tool before recognizing the disguising factor from the spoofed speech helps much to recognize the disguising factor, the proposed framework enables the detection of the disguised voice and the utilized tools. To our knowledge, it is the first attempt, focusing on voice transformation without any prior knowledge of the original speech, to recognize the disguising tool and the disguising factor from the spoofed speech, which is more suitable in real-world applications. Experimental results show that the disguising factors can be recognized with accuracy higher than 90%, indicating a high possibility of restoring the original voice from its disguised counterpart. © 2018 IEEE.

关键词： Convolution

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Quantum-enhanced interferometry with asymmetric beam splitters

arXiv

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arXiv 2020年

作者： Zhong, Wei Wang, Fan Zhou, Lan Xu, Peng Sheng, Yu-Bo Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications Nanjing210003 China National Laboratory of Solid State Microstructures Nanjing University Nanjing210093 China School of Science Nanjing University of Posts and Telecommunications Nanjing210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Nanjing210003 China

In this paper, we investigate the phase sensitivities in two-path optical interferometry with asymmetric beam splitters. Here, we present the optimal conditions for the transmission ratio and the phase of the beam splitter to gain the highest sensitivities for a general class of non-classical states with parity symmetry. Additionally, we address the controversial question of whether the scheme with a combination of coherent state and photon-added or photon-subtracted squeezed vacuum state is better or worse than the most celebrated one using a combination of coherent state and squeezed vacuum state. Copyright © 2020, The Authors. All rights reserved.

关键词： Fisher information matrix

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A Method for Improving CNN-Based Image Recognition Using DCGAN

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Computers, Materials & Continua 2018年第10期57卷 167-178页

作者： Wei Fang Feihong Zhang Victor S.Sheng Yewen Ding School of Computer&Software Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science&TechnologyNanjing210044China State Key Lab.for Novel Software Technology Nanjing UniversityNanjing210023China Computer Science Department University of Central ArkansasConway AR72035USA

Image recognition has always been a hot research topic in the scientific community and *** emergence of convolutional neural networks(CNN)has made this technology turned into research focus on the field of computer vision,especially in image *** it makes the recognition result largely dependent on the number and quality of training ***,DCGAN has become a frontier method for generating images,sounds,and *** this paper,DCGAN is used to generate sample that is difficult to collect and proposed an efficient design method of generating *** combine DCGAN with CNN for the second *** DCGAN to generate samples and training in image recognition model,which based by *** method can enhance the classification model and effectively improve the accuracy of image *** the experiment,we used the radar profile as dataset for 4 categories and achieved satisfactory classification *** paper applies image recognition technology to the meteorological field.

关键词： DCGAN image recognition CNN samples

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Aftershock Detection with Multi-scale Description Based Neural network

Aftershock Detection with Multi-scale Description Based Neur...

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IEEE International Conference on data Mining (ICDM)

作者： Qi Zhang Tong Xu Hengshu Zhu Lifu Zhang Hui Xiong Enhong Chen Qi Liu Anhui Province Key Lab of Big Data Analysis and Application University of Science and Technology of China Baidu Talent Intelligence Center Baidu Inc Business Intelligence Lab Baidu Research

Aftershocks refer to the smaller earthquakes that occur following large earthquakes, in the same area of the main shock. The task of aftershocks detection, as a crucial and challenging issue in disaster monitoring, has attracted wide research attention in relevant fields. Compared with the traditional detection methods like STA/LTA algorithms or heuristic matching, neural network techniques are regarded as an advanced choice with better pattern recognition ability. However, current neural network-based solutions mainly formulate the seismic wave as ordinary time series, where existing techniques are directly deployed without adaption, and thus fail to obtain competitive performance on the intensive and highly-noise waveforms of aftershocks. To that end, in this paper, we propose a novel framework named Multi-Scale Description based Neural network (MSDNN) for enhancing aftershock detection. Specifically, MSDNN contains a delicately-designed network structure for capturing both short-term scale and long-term scale seismic features. Therefore, the unique characteristics of seismic waveforms can be fully-exploited for aftershock detection. Furthermore, a multi-task learning strategy is introduced to model the seismic waveforms of multiple monitoring stations simultaneously, which can not only refine the detection performance but also provide additionally quantitative clues for discovering homologous earthquakes. Finally, comprehensive experiments on the data set from aftershocks of the Wenchuan M8.0 Earthquake have clearly validated the effectiveness of our framework compared with several state-of-the-art baselines.

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Front Cover: International Journal of Intelligent Systems, Volume 37 Issue 11 November 2022

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International Journal of Intelligent Systems 2022年第11期37卷

作者： Xianjia Meng Yong Yang Ximeng Liu Nan Jiang School of Information Science and Technology Northwest University Xi'an People's Republic of China Fujian Province Key Laboratory of Information Security of Network System and College of Computer and Data Science Fuzhou University Fuzhou People's Republic of China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen People's Republic of China Department of Internet of Things School of Information Engineering East China Jiao Tong University Nanchang People's Republic of China

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Cost-Utility Analysis of Screening for Diabetic Retinopathy in China

健康数据科学（英文）

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健康数据科学（英文） 2022年第4期 19-29页

作者： Yue Zhang Weiling Bai Ruyue Li Yifan Du Runzhou Sun Tao Li Hong Kang Ziwei Yang Jianjun Tang Ningli Wang Hanruo Liu Beijing Tongren Eye Center Beijing Key Laboratory of Ophthalmology and Visual SciencesBeijing Tongren HospitalCapital Medical UniversityBeijing Institute of OphthalmologyBeijingChina College of Computer Science Nankai UniversityTianjinChina School of Agricultural Economics and Rural Development Renmin University of ChinaBeijingChina Beijing Tongren Eye Center Beijing Key Laboratory of Ophthalmology and Visual SciencesBeijing Tongren HospitalCapital Medical UniversityBeijing Institute of OphthalmologyBeijingChina National Institute of Health Data Science at Peking University BeijingChina Beijing Institute of Ophthalmology Beijing Tongren HospitalCapital Medical UniversityBeijing Ophthalmology & Visual Science Key LabBeijingChina National Institute of Health Data Science at Peking University BeijingChina Beijing Institute of Ophthalmology Beijing Tongren HospitalCapital Medical UniversityBeijing Ophthalmology & Visual Science Key LabBeijingChina School of Information and Electronics Beijing Institute of TechnologyBeijingChina

*** retinopathy(DR)has been primarily indicated to cause vision impairment and blindness,while no studies have focused on the cost-utility of telemedicine-based and community screening programs for DR in China,especially in rural and urban areas,*** developed a Markov model to calculate the cost-utility of screening programs for DR in DM patients in rural and urban settings from the societal *** incremental cost-utility ratio(ICUR)was calculated for the *** the rural setting,the community screening program obtained 1 QALY with a cost of $4179(95％CI 3859 to 5343),and the telemedicine screening program had an ICUR of $2323(95％CI 1023 to 3903)compared with no screening,both of which satisfied the criterion of a significantly cost-effective health ***,community screening programs in urban areas generated an ICUR of $3812(95％CI 2906 to 4167)per QALY gained,with telemedicine screening at an ICUR of $2437(95％CI 1242 to 3520)compared with no screening,and both were also *** further comparison,compared to community screening programs,telemedicine screening yielded an ICUR of 1212(95％CI 896 to 1590)per incremental QALY gained in rural setting and 1141(95％CI 859 to 1403)in urban setting,which both meet the criterion for a significantly cost-effective health *** telemedicine and community screening for DR in rural and urban settings were cost-effective in China,and telemedicine screening programs were more cost-effective.

关键词： screening analysis china cost-utility diabetic retinopathy

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Explainable fashion recommendation: A semantic attribute region guided approach

arXiv

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arXiv 2019年

作者： Hou, Min Wu, Le Chen, Enhong Li, Zhi Zheng, Vincent W. Liu, Qi Anhui Province Key Lab. of Big Data Analysis and Application University of S&T of China School of Data Science University of S&T of China Hefei University of Technology WeBank

In fashion recommender systems, each product usually consists of multiple semantic attributes (e.g., sleeves, collar, etc). When making cloth decisions, people usually show preferences for different semantic attributes (e.g., the clothes with v-neck collar). Nevertheless, most previous fashion recommendation models comprehend the clothing images with a global content representation and lack detailed understanding of users' semantic preferences, which usually leads to inferior recommendation performance. To bridge this gap, we propose a novel Semantic Attribute Explainable Recommender System (SAERS). Specifically, we first introduce a fine-grained interpretable semantic space. We then develop a Semantic Extraction network (SEN) and Fine-grained Preferences Attention (FPA) module to project users and items into this space, respectively. With SAERS, we are capable of not only providing cloth recommendations for users, but also explaining the reason why we recommend the cloth through intuitive visual attribute semantic highlights in a personalized manner. Extensive experiments conducted on realworld datasets clearly demonstrate the effectiveness of our approach compared with the state-ofthe-art methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Recommender systems

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Co-whitening of i-vectors for short and long duration speaker verification 19

Co-whitening of i-vectors for short and long duration speake...

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19th Annual Conference of the International Speech Communication, INTERSPEECH 2018

作者： Xu, Longting Lee, Kong Aik Li, Haizhou Yang, Zhen Department of Electrical and Computer Engineering National University of Singapore Singapore Data Science Research Laboratories NEC Corporation Japan Broadband Wireless Communication and Sensor Network Technology Key Lab Nanjing University of Posts and Telecommunications China

An i-vector is a fixed-length and low-rank representation of a speech utterance. It has been used extensively in text-independent speaker verification. Ideally, speech utterances from the same speaker would map to an unique i-vector. However, this is not the case due to some intrinsic and extrinsic factors like physical condition of the speaker, channel difference, noise and notably the duration of speech utterances. In particular, we found that i-vectors extracted from short utterances exhibit larger variance than that of long utterances. To address the problem, we propose a co-whitening approach, taking into account the duration, while maximizing the correlation between the i-vectors of short and long duration. The proposed co-whitening method was derived based on canonical correlation analysis (CCA). Experimental results on NIST SRE 2010 show that co-whitening method is effective in compensating the duration mismatch, leading to a reduction of up to 13.07% in equal error rate (EER). © 2018 International Speech Communication Association. All rights reserved.

关键词： Vectors

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