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2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014

作者： Guo, Dongyan Zhang, Jian Xu, Min He, Xiangjian Li, Minxian Zhao, Chunxia School of Computer Science and Engineering Nanjing University of Science and Technology China Advanced Analytics Institute and School of Software University of Technology Sydney Australia University of Technology Sydney Australia

ISBN: (纸本)9781479954094

Playing a vital role, saliency has been widely applied for various image analysis tasks, such as content-aware image retargeting, image retrieval and object detection. It is generally accepted that saliency detection can benefit from the integration of multiple visual features. However, most of the existing literatures fuse multiple features at saliency map level without considering cross-feature information, i.e. generate a saliency map based on several maps computed from an individual feature. In this paper, we propose a Multiple Feature Distance Preserving (MFDP) model to seamlessly integrate multiple visual features through an alternative optimization process. Our method outperforms the state-of-the-arts methods on saliency detection. Saliency detected by our method is further cooperated with seam carving algorithm and significantly improves the performance on image retargeting. © 2014 IEEE.

关键词： Image retrieval

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Scientific Article Recommendation: Exploiting Common Author Relations and Historical Preferences

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IEEE Transactions on Big Data 2016年第2期2卷 101-112页

作者： Xia, Feng Liu, Haifeng Lee, Ivan Cao, Longbing School of Software Dalian University of Technology Dalian116620 China School of Information Technology and Mathematical Sciences University of South Australia0 AdelaideSA5001 Australia Advanced Analytics Institute University of Technology SydneyNSW2007 Australia

Scientific article recommender systems are playing an increasingly important role for researchers in retrieving scientific articles of interest in the coming era of big scholarly data. Most existing studies have designed unified methods for all target researchers and hence the same algorithms are run to generate recommendations for all researchers no matter which situations they are in. However, different researchers may have their own features and there might be corresponding methods for them resulting in better recommendations. In this paper, we propose a novel recommendation method which incorporates information on common author relations between articles (i.e., two articles with the same author(s)). The rationale underlying our method is that researchers often search articles published by the same author(s). Since not all researchers have such author-based search patterns, we present two features, which are defined based on information about pairwise articles with common author relations and frequently appeared authors, to determine target researchers for recommendation. Extensive experiments we performed on a real-world dataset demonstrate that the defined features are effective to determine relevant target researchers and the proposed method generates more accurate recommendations for relevant researchers when compared to a Baseline method. © 2015 IEEE.

关键词： Collaborative filtering

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Applying client churn prediction modeling on home-based care services industry

Applying client churn prediction modeling on home-based care...

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International Conference on Behavior, Economic and Socio-cultural Computing

作者： Raul Manongdo Guandong Xu Advanced Analytics Institute University of Technology Sydney Australia School of Software and Advanced Analytics Institute University of Technology Sydney Australia

ISBN: (纸本)9781509061655

Client churn prediction model is widely acknowledged as an effective way of realizing customer life-time value especially in service-oriented industries and under a competitive business environment. Churn model allows targeting of clients for retention campaigns and is a critical component of customer relationship management (CRM) and business intelligence systems. There are numerous statistical models and techniques applied successfully on data mining projects for various industries. While there is literature for prediction modeling on hospital health care services, non-exist for home-based care services. In this study, logistic regression, random forest and C5.0 decision tree were the models used in building a binary client churn classifier for a home-based care services company based in Australia. All models yielded prediction accuracies over 90% with tree based classifiers marginally higher and C5.0 model found to be suitable for use in this industry. This study also showed that existing client satisfaction measures currently in use by the company does not adequately contribute to churn analysis.

关键词： Companies Predictive models Industries Discharges (electric) Logistics Monitoring Decision trees Prediction models Decision Trees Churn Logistics Companies industries customers Clients Legal Services Patient Satisfaction statistical models (nuclear) Power grids Business intelligence

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Efficient people counting with limited manual interferences

Efficient people counting with limited manual interferences

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2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014

作者： Xu, Jingsong Wu, Qiang Zhang, Jian Silk, Boreak Ngo, Gia Thuan Tang, Zhenmin School of Computer Science and Engineering Nanjing University of Science and Technology China School of Computing and Communications University of Technology Sydney Australia Advanced Analytics Institute and School of Software University of Technology Sydney Australia City Research City of Melbourne Australia

ISBN: (纸本)9781479954094

People counting is a topic with various practical applications. Over the last decade, two general approaches have been proposed to tackle this problem: a) counting based on individual human detection;b)counting by measuring regression relation between the crowd density and number of people. Because the regression based method can avoid explicit people detection which faces several well-known challenges, it has been considered as a robust method particularly on a complicated environments. An efficient regression based method is proposed in this paper, which can be well adopted into any existing video surveillance system. It adopts color based segmentation to extract foreground regions in images. Regression is established based on the foreground density and the number of people. This method is fast and can deal with lighting condition changes. Experiments on public datasets and one captured dataset have shown the effectiveness and robustness of the method. © 2014 IEEE.

关键词： Image segmentation

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SKRWM based descriptor for pedestrian detection in thermal images

SKRWM based descriptor for pedestrian detection in thermal i...

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3rd IEEE International Workshop on Multimedia Signal Processing, MMSP 2011

作者： Li, Zelin Wu, Qiang Zhang, Jian Geers, Glenn National ICT Australia University of New South Wales Australia School of Computer Science and Engineering University of New South Wales Australia School of Computing and Communications University of Technology Sydney NSW Australia Advanced Analytics Institute School of Software University of Technology Sydney NSW Australia

ISBN: (纸本)9781457714337

Pedestrian detection in a thermal image is a difficult task due to intrinsic challenges:1) low image resolution, 2) thermal noising, 3) polarity changes, 4) lack of color, texture or depth information. To address these challenges, we propose a novel mid-level feature descriptor for pedestrian detection in thermal domain, which combines pixel-level Steering Kernel Regression Weights Matrix (SKRWM) with their corresponding covariances. SKRWM can properly capture the local structure of pixels, while the covariance computation can further provide the correlation of low level feature. This mid-level feature descriptor not only captures the pixel-level data difference and spatial differences of local structure, but also explores the correlations among low-level features. In the case of human detection, the proposed mid-level feature descriptor can discriminatively distinguish pedestrian from complexity. For testing the performance of proposed feature descriptor, a popular classifier framework based on Principal Component Analysis (PCA) and Support Vector Machine (SVM) is also built. Overall, our experimental results show that proposed approach has overcome the problems caused by background subtraction in [1] while attains comparable detection accuracy compared to the state-of-the-arts. © 2011 IEEE.

关键词： Image resolution

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Locally private Jaccard similarity estimation

Locally private Jaccard similarity estimation

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作者： Yan, Ziqi Wu, Qiong Ren, Meng Liu, Jiqiang Liu, Shaowu Qiu, Shuo Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing100044 China School of Computer Science Xi'an Shiyou University Xi'an710065 China Advanced Analytics Institute University of Technology Sydney Ultimo2007 Australia School of Software Engineering Jinling Institute of Technology Nanjing211169 China

Jaccard Similarity has been widely used to measure the distance between two sets (or preference profiles) owned by two different users. Yet, in the private data collection scenario, it requires the untrusted curator could only estimate an approximately accurate Jaccard similarity of the involved users but without being allowed to access their preference profiles. This paper aims to address the above requirements by considering the local differential privacy model. To achieve this, we initially focused on a particular hash technique, MinHash, which was originally invented to estimate the Jaccard similarity efficiently. We designed the PrivMin algorithm to achieve the perturbation of MinHash signature by adopting Exponential mechanism and build the Locally Differentially Private Jaccard Similarity Estimation (LDP-JSE) protocol for allowing the untrusted curator to approximately estimate Jaccard similarity. Theoretical and empirical results demonstrate that the proposed protocol can retain a highly acceptable utility of the estimated similarity as well as preserving privacy. © 2018 John Wiley & Sons, Ltd.

关键词： Jaccard similarity local differential privacy MinHash

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NetSim – The framework for complex network generator

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Procedia Computer Science 2018年 126卷 547-556页

作者： Akanda Wahid-Ul-Ashraf Marcin Budka Katarzyna Musial Department of Computing and Informatics Bournemouth University Fern Barrow Poole BH12 5BB UK Advanced Analytics Institute School of Software Faculty of Engineering and IT University of Technology Sydney Australia

Networks are everywhere and their many types, including social networks, the Internet, food webs etc., have been studied for the last few decades. However, in real-world networks, it’s hard to find examples that can be easily comparable, i.e. have the same density or even number of nodes and edges. We propose a flexible and extensible NetSim framework to understand how properties in different types of networks change with varying number of edges and vertices. Our approach enables to simulate three classical network models (random, small-world and scale-free) with easily adjustable model parameters and network size. To be able to compare different networks, for a single experimental setup we kept the number of edges and vertices fixed across the models. To understand how they change depending on the number of nodes and edges we ran over 30,000 simulations and analysed different network characteristics that cannot be derived analytically. Two of the main findings from the analysis are that the average shortest path does not change with the density of the scale-free network but changes for small-world and random networks; the apparent difference in mean betweenness centrality of the scale-free network compared with random and small-world networks.

关键词： complex networks simulation random graphs scale-free networks small-world networks

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A Smart Assistive Device for the Blind People 7th

A Smart Assistive Device for the Blind People

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7th International Conference on Information and Communication Technology for Competitive Strategies , ICTCS 2022

作者： Valarmathi, B. Gupta, N. Srinivasa Chellatamilan, T. Santhi, K. Reddy, R. Hemadri Department of Software and Systems Engineering School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Analytics School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Mathematics School of Advanced Sciences Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9789811996375

Mobility is the biggest issue for blind individuals. In order to move around, they must rely on others. Therefore, we are creating a navigational aid for blind people, to help the blind people in the world from various difficulties they face in day-to-day life. The World Health Organization (WHO) reported that a survey was conducted in 2014 and that there are an estimated 285 million visually impaired persons worldwide, of which 37 million are blind, with over 15 million of them being Indian. The majority of blind persons depend on other people for their activities since INDIA accounts for 21% of the global population of blind people (Khanam et al. in Int J Adv Res Sci Eng 7:195–199, 2018). Smart shoes play an important role. Obstacle detection is performed using ultrasonic sensor which is also done by many people in the previous projects or researches. The new concept that is included in this paper is that it can also detect any flame and potholes around the person using flame sensor and ultrasonic sensor, respectively. And we use shock sensor to detect any shock that occurs. If the smart assistive device or smart shoes senses an object, a pothole, a fire (from about three feet away), or a shock in front of the user, a buzzer will sound. These sensors are integrated using Arduino Uno. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Obstacle detectors

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Multiple Kernel Learning Based Multi-view Spectral Clustering

Multiple Kernel Learning Based Multi-view Spectral Clusterin...

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International Conference on Pattern Recognition

作者： Dongyan Guo Jian Zhang Xinwang Liu Ying Cui Chunxia Zhao School of Computer Science and Engineering Nanjing University of Science and Technology China Advanced Analytics Institute & School of Software University of Technology Sydney Australia School of Computer National University of Defense Technology China

ISBN: (纸本)9781479952106

For a given data set, exploring their multi-view instances under a clustering framework is a practical way to boost the clustering performance. This is because that each view might reflect partial information for the existing data. Furthermore, due to the noise and other impact factors, exploring these instances from different views will enhance the mining of the real structure and feature information within the data set. In this paper, we propose a multiple kernel spectral clustering algorithm through the multi-view instances on the given data set. By combining the kernel matrix learning and the spectral clustering optimization into one process framework, the algorithm can determine the kernel weights and cluster the multi-view data simultaneously. We compare the proposed algorithm with some recent published methods on real-world datasets to show the efficiency of the proposed algorithm.

关键词： Kernel Clustering algorithms Optimization Linear programming Clustering methods Educational institutions Proteins

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A Multiple Features Distance Preserving (MFDP) Model for Saliency Detection

A Multiple Features Distance Preserving (MFDP) Model for Sal...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Dongyan Guo Jian Zhang Min Xu Xiangjian He Minxian Li Chunxia Zhao School of Computer Science and Engineering Nanjing University of Science and Technology China Advanced Analytics Institute & School of Software University of Technology Sydney Australia Center for Innovation in IT Services and Applications (iNEXT) University of Technology Sydney Australia

ISBN: (纸本)9781479954100

关键词： Feature extraction Visualization Mathematical model Image color analysis Equations Educational institutions Computational modeling

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