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arXiv 2018年

作者： Ahn, Ho Seok Dayoub, Feras Popović, Marija MacDonald, Bruce A. Siegwart, Roland Sa, Inkyu Department of Electrical and Computer Engineering CARES University of Auckland 368 Khyber Pass Rd Newmarket Auckland1023 New Zealand Department of Mechanical and Process Engineering Institute of Robotics and Intelligent Systems Autonomous Systems Lab. ETH Zurich Switzerland

Horticultural enterprises are becoming more sophisticated as the range of the crops they target expands. Requirements for enhanced efficiency and productivity have driven the demand for automating on-field operations. However, various problems remain yet to be solved for their reliable, safe deployment in real-world scenarios. This paper examines major research trends and current challenges in horticultural robotics. Specifically, our work focuses on sensing and perception in the three main horticultural procedures: Pollination, yield estimation, and harvesting. For each task, we expose major issues arising from the unstructured, cluttered, and rugged nature of field environments, including variable lighting conditions and difficulties in fruit-specific detection, and highlight promising contemporary studies. Based on our survey, we address new perspectives and discuss future development trends. Copyright © 2018, The Authors. All rights reserved.

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Lingke: A fine-grained multi-turn chatbot for customer service

arXiv

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arXiv 2018年

作者： Zhu, Pengfei Zhang, Zhuosheng Li, Jiangtong Huang, Yafang Zhao, Hai School of Computer Science and Software Engineering East China Normal University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai200240 China College of Zhiyuan Shanghai Jiao Tong University China

Traditional chatbots usually need a mass of human dialogue data, especially when using supervised machine learning method. Though they can easily deal with single-turn question answering, for multi-turn the performance is usually unsatisfactory. In this paper, we present Lingke, an information retrieval augmented chatbot which is able to answer questions based on given product introduction document and deal with multi-turn conversations. We will introduce a finegrained pipeline processing to distill responses based on unstructured documents, and attentive sequential context-response matching for multi-turn conversations. Copyright © 2018, The Authors. All rights reserved.

关键词： Supervised learning

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WISERNet: Wider Separate-then-reunion Network for Steganalysis of Color Images

arXiv

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arXiv 2018年

作者： Zeng, Jishen Tan, Shunquan Liu, Guangqing Li, Bin Huang, Jiwu Guangdong Key Laboratory of Intelligent Information Processing National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China College of Computer Science and Software Engineering Shenzhen University Guangdong Key Lab. of Intelligent Info. Processing and Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen518060 China Peng Cheng Laboratory Shenzhen518052 China

Until recently, deep steganalyzers in spatial domain have been all designed for gray-scale images. In this paper, we propose WISERNet (the wider separate-then-reunion network) for steganalysis of color images. We provide theoretical rationale to claim that the summation in normal convolution is one sort of "linear collusion attack" which reserves strong correlated patterns while impairs uncorrelated noises. Therefore in the bottom convolutional layer which aims at suppressing correlated image contents, we adopt separate channel-wise convolution without summation instead. Conversely, in the upper convolutional layers we believe that the summation in normal convolution is beneficial. Therefore we adopt united normal convolution in those layers and make them remarkably wider to reinforce the effect of "linear collusion attack". As a result, our proposed wide-and-shallow, separate-then-reunion network structure is specifically suitable for color image steganalysis. We have conducted extensive experiments on color image datasets generated from BOSSBase raw images and another large-scale dataset which contains 100,000 raw images, with di_erent demosaicking algorithms and downsampling algorithms. The experimental results show that our proposed network outperforms other state-of-the-art color image steganalytic models either hand-crafted or learned using deep networks in the literature by a clear margin. Specifically, it is noted that the detection performance gain is achieved with less than half the complexity compared to the most advanced deeplearning steganalyzer as far as we know, which is scarce in the literature. Copyright © 2018, The Authors. All rights reserved.

关键词： Steganography

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Modeling Multi-turn conversation with deep utterance aggregation

arXiv

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arXiv 2018年

作者： Zhang, Zhuosheng Li, Jiangtong Zhu, Pengfei Zhao, Hai Liu, Gongshen Department of Computer Science and Engineering Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai200240 College of Zhiyuan Shanghai Jiao Tong University School of Cyber Security Shanghai Jiao Tong University School of Computer Science and Software Engineering East China Normal University

Multi-turn conversation understanding is a major challenge for building intelligent dialogue systems. This work focuses on retrieval-based response matching for multi-turn conversation whose related work simply concatenates the conversation utterances, ignoring the interactions among previous utterances for context modeling. In this paper, we formulate previous utterances into context using a proposed deep utterance aggregation model to form a fine-grained context representation. In detail, a self-matching attention is first introduced to route the vital information in each utterance. Then the model matches a response with each refined utterance and the final matching score is obtained after attentive turns aggregation. Experimental results show our model outperforms the state-of-the-art methods on three multi-turn conversation benchmarks, including a newly introduced e-commerce dialogue corpus. Copyright © 2018, The Authors. All rights reserved.

关键词： Speech processing

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Deep User Modeling for Content-based Event Recommendation in Event-based Social Networks

Deep User Modeling for Content-based Event Recommendation in...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Zhibo Wang Yongquan Zhang Honglong Chen Zhetao Li Feng Xia Jiangsu Key Lab. of Big Data Security & Intelligent Processing NJUPT P. R. China School of Cyber Science and Engineering Wuhan University P. R. China College of Information and Control Engineering China University of Petroleum P. R. China College of Information Engineering Xiangtan University P. R. China School of Software Dalian University of Technology P. R. China

ISBN: (纸本)9781538641293

Event-based social networks (EBSNs) are the newly emerging social platforms for users to publish events online and attract others to attend events offline. The content information of events plays an important role in event recommendation. However, the content-based approaches in existing event recommender systems cannot fully represent the preference of each user on events since most of them focus on exploiting the content information from events' perspective, and the bag-of-words model, commonly used by them, can only capture word frequency but ignore word orders and sentence structure. In this paper, we shift the focus from events' perspective to users' perspective, and propose a Deep User Modeling framework for Event Recommendation (DUMER) to characterize the preference of users by exploiting the contextual information of events that users have attended. Specifically, we utilize convolutional neural network (CNN) with word embedding to deeply capture the contextual information of a user's interested events and build up a user latent model for each user. We then incorporate the user latent model into probabilistic matrix factorization (PMF) model to enhance the recommendation accuracy. We conduct experiments on the real-world dataset crawled from a typical EBSN, ***, and the experimental results show that DUMER outperforms the compared benchmarks.

关键词： Recommender systems Machine learning Social network services Feature extraction Context modeling Conferences Probabilistic logic

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Appearance of a robot affects the impact of its behaviour on perceived trustworthiness and empathy

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Paladyn 2016年第1期7卷 55-66页

作者： Zlotowski, Jakub Sumioka, Hidenobu Nishio, Shuichi Glas, Dylan F. Bartneck, Christoph Ishiguro, Hiroshi HIT Lab. NZ University of Canterbury Christchurch New Zealand Hiroshi Ishiguro Laboratory Advanced Telecommunications Research Institute International Kyoto Japan Intelligent Robotics and Communication Laboratories Advanced Telecommunications Research Institute International Kyoto Japan Department of System Innovation Graduate School of Engineering Science Osaka University Osaka Japan

An increasing number of companion robots have started reaching the public in the recent years. These robots vary in their appearance and behavior. Since these two factors can have an impact on lasting human-robot relationships, it is important to understand their effect for companion robots. We have conducted an experiment that evaluated the impact of a robot's appearance and its behaviour in repeated interactions on its perceived empathy, trustworthiness and anxiety experienced by a human. The results indicate that a highly humanlike robot is perceived as less trustworthy and empathic than a more machinelike robot. Moreover, negative behaviour of a machinelike robot reduces its trustworthiness and perceived empathy stronger than for highly humanlike robot. In addition, we found that a robot which disapproves of what a human says can induce anxiety felt towards its communication capabilities. Our findings suggest that more machinelike robots can be more suitable as companions than highly humanlike robots. Moreover, a robot disagreeing with a human interaction partner should be able to provide feedback on its understanding of the partner's message in order to reduce her anxiety. © 2016 Jakub Zlotowski et al., published by De Gruyter Open.

关键词： Human robot interaction

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Scalab.e and user-friendly simulation 29

Scalable and user-friendly simulation

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29th European Conference on Modelling and Simulation, ECMS 2015

作者： Rutle, Adrian Wang, Hao Bye, Robin T. Osen, Ottar L. Department of Computing Mathematics and Physics Bergen University College Postboks 7030 BergenNO-5020 Norway Big Data Lab. Aalesund University College Norway Software and Intelligent Control Engineering Lab. Aalesund University College Norway Faculty of Engineering and Natural Sciences Aalesund University College Norway

ISBN: (纸本)9780993244001

Simulation is an important technique for integrating interacting models for predicting results of hypothetical scenarios. A typical application area for simulators is virtual prototyping (VP). In VP, simulators replace the real-world prototype. Hence, the quality of the virtual prototype depends on the quality of its simulations, which in turn are highly dependent on the quality of the models and the computational power, especially if visualization and/or real-time constraints are required. Unfortunately defining models is an error-prone activity which requires domain-experts to have knowledge about the implementation details and/or IT-technical concerns. In addition, the bigger the dataset, the more computational power is needed, which affects the cost, and in turn, the usability of today's simulators. To address both of these aspects, we propose a user-friendly, adaptive and scalab.e agent-based modelling and simulation framework with a hybrid CPU/GPU/FPGA high performance computing platform. The solution we describe provides domain-experts with a a scalab.e, adaptive, and efficient simulator and enables domain-experts to define high quality models without in-depth IT-knowledge. We use a running example from the particle transmission domain to illustrate our approach. © ECMS Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova (Editors).

关键词： Scalab.lity

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Social sensing enhanced time estimation for bus service

Social sensing enhanced time estimation for bus service

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作者： Liu, Jin Li, Juan Cui, Xiaohui Niu, Xiaoguang Sun, Xiaoping Zhou, Jing State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEAs and road condition attributions PRCAs. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEAs of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. © 2015 John Wiley & Sons, Ltd.

关键词： Buses

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Decoding of color coded structured light using a new color feature 4

Decoding of color coded structured light using a new color f...

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4th International Workshop of Advanced Manufacturing and Automation, IWAMA 2014

作者： Tang, Su Ming Zhang, Xu Tu, Da Wei School of Mechatronic Engineering and Automation Shanghai University Shanghai China State Key Lab. of Digital Manufacturing Equipment and Technology in Huazhong University of Science Technology Wuhan China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China

ISBN: (纸本)9783038352532

In this paper, color coded structured light based on pseudo-random sequence is adopted, and a new decoding method is proposed. It includes three steps. First, the stripe centers are extracted through the use of peak detection. Second, the stripe colors are identified using k-means clustering algorithm on a new color feature with high discriminating power. This feature is related to the spectral sensitivity of red, green and blue sensors, the direction of the illumination source, the normal and albedo of the surface, and the spectral power distribution of the incident light, but it is insensitive to the intensity. Finally, a four-step matching method is presented in sequence matching, which is aim to match the subsequences with the length less than the window size. The experimental results show that our proposed decoding method has advantage of high accuracy. © (2014) Trans Tech Publications, Switzerland.

关键词： Color

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Control of robotic arm manipulator with haptic feedback using programmable system on chip

Control of robotic arm manipulator with haptic feedback usin...

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International Conference on robotics and Emerging Allied Technologies in engineering (iCREATE)

作者： Muhammad Yaqoob Sardar Rushan Qaisrani Muhammad Waqas Yasar Ayaz Sohail Iqbal Sajid Nisar Department of Electrical Engineering National University of Sciences and Technology (NUST) Islamabad Pakistan Robotics & Intelligent Systems Engineering (RISE) Lab. National University of Sciences and Technology (NUST) Islamabad Pakistan

Programmable system on chip (PSoC) is used to control six degree of freedom robotic arm manipulator with haptic or force feedback system. Polar coordinates system is used to cover three dimensional space by robotic arm manipulator. Primarily use of this system is in intelligent industrial manufacturing, gaming industry and most importantly robots assisted surgery. Master-slave control topology is used along with 2-way feedback. PSoC is used to monitor state of force sensors and digital encoders mounted on robotic manipulator. Along with monitoring it also used to manipulate these values according to 2-way feedback between master-slave control topology. Experimental results representing force feedback are shown in the graphical userinterface.

关键词： Robot kinematics Haptic interfaces Grippers Force Hardware Robot sensing systems

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