检索结果-内蒙古大学图书馆

arXiv 2018年

作者： Min, Weiqing Jiang, Shuqiang Liu, Linhu Rui, Yong Jain, Ramesh Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China Lenovo Group No. 6 Shangdi West Road Beijing China Department of Computer Science University of California IrvineCA United States

Food is very essential for human life and it is fundamental to the human experience. Food-related study may support multifarious applications and services, such as guiding the human behavior, improving the human health and understanding the culinary culture. With the rapid development of social networks, mobile networks, and Internet of Things (IoT), people commonly upload, share, and record food images, recipes, cooking videos, and food diaries, leading to large-scale food data. Large-scale food data offers rich knowledge about food and can help tackle many central issues of human society. Therefore, it is time to group several disparate issues related to food computing. Food computing acquires and analyzes heterogenous food data from disparate sources for perception, recognition, retrieval, recommendation, and monitoring of food. In food computing, computational approaches are applied to address food related issues in medicine, biology, gastronomy and agronomy. Both large-scale food data and recent breakthroughs in computer science are transforming the way we analyze food data. Therefore, vast amounts of work has been conducted in the food area, targeting different food-oriented tasks and applications. However, there are very few systematic reviews, which shape this area well and provide a comprehensive and in-depth summary of current efforts or detail open problems in this area. In this paper, we formalize food computing and present such a comprehensive overview of various emerging concepts, methods, and tasks. We summarize key challenges and future directions ahead for food computing. This is the first comprehensive survey that targets the study of computing technology for the food area and also offers a collection of research studies and technologies to benefit researchers and practitioners working in different food-related fields. Copyright © 2018, The Authors. All rights reserved.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

Attentionxml: label tree-based attention-aware deep model for high-performance extreme multi-label text classification

arXiv

引用

arXiv 2018年

作者： You, Ronghui Zhang, Zihan Wang, Ziye Dai, Suyang Mamitsuka, Hiroshi Zhu, Shanfeng Shanghai Key Lab of Intelligent Information Processing School of Computer Science Centre for Computational Systems Biology School of Mathematical Sciences Shanghai Institute of Artificial Intelligence Algorithms and ISTBI Fudan University Shanghai China Bioinformatics Center Institute for Chemical Research Kyoto University Japan Department of Computer Science Aalto University Helsinki Finland

Extreme multi-label text classification (XMTC) is an important problem in the era of big data, for tagging a given text with the most relevant multiple labels from an extremely large-scale label set. XMTC can be found in many applications, such as item categorization, web page tagging, and news annotation. Traditionally most methods used bag-of-words (BOW) as inputs, ignoring word context as well as deep semantic information. Recent attempts to overcome the problems of BOW by deep learning still suffer from 1) failing to capture the important subtext for each label and 2) lack of scalability against the huge number of labels. We propose a new label tree-based deep learning model for XMTC, called AttentionXML, with two unique features: 1) a multi-label attention mechanism with raw text as input, which allows to capture the most relevant part of text to each label;and 2) a shallow and wide probabilistic label tree (PLT), which allows to handle millions of labels, especially for "tail labels". We empirically compared the performance of AttentionXML with those of eight state-of-the-art methods over six benchmark datasets, including Amazon-3M with around 3 million labels. AttentionXML outperformed all competing methods under all experimental settings. Experimental results also show that AttentionXML achieved the best performance against tail labels among label tree-based methods. The code and datasets are available at http://***/yourh/AttentionXML . Copyright © 2018, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Denoising of 3D magnetic resonance images using a residual encoder-decoder wasserstein generative adversarial network

arXiv

引用

arXiv 2018年

作者： Ran, Maosong Hu, Jinrong Chen, Yang Chen, Hu Sun, Huaiqiang Zhou, Jiliu Zhang, Yi College of Computer Science Sichuan University Chengdu610065 China Department of Computer Science Chengdu University of Information Technology Chengdu610225 China Lab of Image Science and Technology School of Computer Science and Engineering Southeast University Nanjing210096 China School of Cyber Science and Engineering Southeast University Nanjing210096 China Ministry of Education Nanjing210096 China Department of Radiology West China Hospital of Sichuan University Chengdu610041 China Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University Guangzhou510515 China

Structure-preserved denoising of 3D magnetic resonance imaging (MRI) images is a critical step in medical image analysis. Over the past few years, many algorithms with impressive performances have been proposed. In this paper, inspired by the idea of deep learning, we introduce an MRI denoising method based on the residual encoder-decoder Wasserstein generative adversarial network (RED-WGAN). Specifically, to explore the structure similarity between neighboring slices, a 3D configuration is utilized as the basic processing unit. Residual autoencoders combined with deconvolution operations are introduced into the generator network. Furthermore, to alleviate the oversmoothing shortcoming of the traditional mean squared error (MSE) loss function, the perceptual similarity, which is implemented by calculating the distances in the feature space extracted by a pretrained VGG-19 network, is incorporated with the MSE and adversarial losses to form the new loss function. Extensive experiments are implemented to assess the performance of the proposed method. The experimental results show that the proposed RED-WGAN achieves performance superior to several state-of-the-art methods in both simulated and real clinical data. In particular, our method demonstrates powerful abilities in both noise suppression and structure preservation. Copyright © 2018, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

A dynamic mining algorithm for multi-granularity user’s learning preference based on ant colony optimization 2nd

A dynamic mining algorithm for multi-granularity user’s lea...

引用

2nd IFIP TC 12 International Conference on Intelligence science, ICIS 2017

作者： Liu, Shengjun Chen, Shengbing Meng, Hu Anhui USTC-GZ Information Technology Co. Ltd. Hefei230031 China Key Lab of Network and Intelligent Information Processing Department of Computer Science and Technology Hefei University Hefei230601 China HEFEI City Cloud Data Center Co. Ltd. Hefei230094 China

ISBN: (纸本)9783319681207

Mining user’s learning preference is one of the key issues in the personalized online learning system, which is of great significance technology for modern educational. In this paper, using the hierarchical characteristics of the knowledge points in the course domain, we defined the equivalence relation and equivalence of knowledge points, and defined the structure of the knowledge points quotient space. Then, the functions of support, pheromone concentration and preference were defined on various levels, and an improved ant colony optimization was proposed to handle the multi granularity data structure of quotient space. An algorithm of multi-granularity Learning Preference Mining based on Ant Colony Optimization (ACO-LPM) was proposed to address the problems about too many learning knowledge points and too few user’s test data in the online personalized learning system. The pheromone has the characteristic of dynamic evaporation, so, the preference patterns mined by ACO-LPM can be changed with the change of user interest in real time. The experimental results show that the algorithm can mining the user’s learning preferences in online learning system effectively and efficiently. © IFIP International Federation for information processing 2017.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

Methods and measurements to compare men against machines

Methods and measurements to compare men against machines

引用

Human Vision and Electronic Imaging 2017, HVEI 2017

作者： Wichmann, Felix A. Janssen, David H.J. Geirhos, Robert Aguilar, Guillermo Schütt, Heiko H. Maertens, Marianne Bethge, Matthias Neural Information Processing Group University of Tübingen Germany Bernstein Center for Computational Neuroscience Tübingen Germany Max Planck Institute for Intelligent Systems Tübingen Germany Faculty of Computer Science and Electrical Engineering TU Berlin Germany Bernstein Center for Computational Neuroscience Berlin Germany Department of Psychology University of Potsdam Germany Centre for Integrative Neuroscience University of Tübingen Germany

Recent advances in computational models in vision science have considerably furthered our understanding of human visual perception. At the same time, rapid advances in convolutional deep neural networks (DNNs) have resulted in computer vision models of object recognition which, for the first time, rival human object recognition. Furthermore, it has been suggested that DNNs may not only be successful models for computer vision, but may also be good computational models of the monkey and human visual systems. The advances in computational models in both vision science and computer vision pose two challenges in two different and independent domains: First, because the latest computational models have much higher predictive accuracy, and competing models may make similar predictions, we require more human data to be able to statistically distinguish between different models. Thus we would like to have methods to acquire trustworthy human behavioural data fast and easy. Second, we need challenging experiments to ascertain whether models show similar input-output behaviour only near "ceiling" performance, or whether their performance degrades similar to human performance: only then do we have strong evidence that models and human observers may be using similar features and processing strategies. In this paper we address both challenges. © 2017, Society for Imaging science and Technology.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Secrecy performance analysis of SIMO underlay cognitive radio systems with outdated CSI

引用

IET Communications 2017年第12期11卷 1961-1969页

作者： Lei, Hongjiang Zhang, Jianming Park, Ki-Hong Ansari, Imran Shafique Pan, Gaofeng Alouini, Mohamed-Slim Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Department of Electrical and Computer Engineering (ECEN) Texas A and M University at Qatar (TAMUQ) Education City Doha Qatar Chongqing Key Laboratory of Non-linear Circuits and Intelligent Information Processing Southwest University Chongqing 400715 China

This study investigates the secrecy outage performance of a single-input multiple-output underlay cognitive radio network (CRN) with outdated channel state information (CSI). The confidential messages are transmitted from transmitter to the destination, while a multi-antenna eavesdropper exists. The maximal ratio combining and selection combining schemes are utilised at the receivers to improve the quality of the received signal-to-noise ratio. The exact and asymptotic closed-form expressions of secrecy outage probability are derived, and simulation results are provided to verify the authors' proposed analytical results. The results reveal that imperfect CSI of main channels deteriorates the secrecy outage performance while that of eavesdropping and interfering channels has contrary effect, and only a unity diversity order can be obtained in underlay CRNs with imperfect CSI. © The Institution of Engineering and Technology.

关键词： antenna arrays cognitive radio diversity reception probability radio networks telecommunication security

来源：评论

学校读者我要写书评

暂无评论

POSTER: Provably Efficient Scheduling of Cache-Oblivious Wavefront Algorithms

引用

ACM SIGPLAN Notices 2017年第8期52卷 435-436页

作者： Chowdhury, Rezaul Ganapathi, Pramod Tang, Yuan Tithi, Jesmin Jahan Department of Computer Science Stony Brook University New York United States School of Software Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai China Intel Corporation

Standard cache-oblivious recursive divide-and-conquer algorithms for evaluating dynamic programming recurrences have optimal serial cache complexity but often have lower parallelism compared with iterative wavefront algorithms due to artificial dependencies among subtasks. Very recently cache-oblivious recursive wavefront (COW) algorithms have been introduced which do not have any artificial dependencies. Though COW algorithms are based on fork-join primitives, they extensively use atomic operations, and as a result, performance guarantees provided by state-of-the-art schedulers for programs with fork-join primitives do not apply. In this work, we show how to systematically transform standard cache-oblivious recursive divide-and-conquer algorithms into recursive wavefront algorithms to achieve optimal parallel cache complexity and high parallelism under state-of-the-art schedulers for fork-join programs. Unlike COW algorithms these new algorithms do not use atomic operations. Instead, they use closed-form formulas to compute at what time each recursive function must be launched in order to achieve high parallelism without losing cache performance. The resulting implementations are arguably much simpler than implementations of known COW algorithms. © 2017 ACM.

关键词： Dynamic programming

来源：评论

学校读者我要写书评

暂无评论

From social to individuals: A parsimonious path of multi-level models for crowdsourced preference aggregation

arXiv

引用

arXiv 2018年

作者： Xu, Qianqian Xiong, Jiechao Cao, Xiaochun Huang, Qingming Yao, Yuan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing1000190 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Tencent AI Lab Shenzhen518057 BICMR-LMAM-LMEQF-LMP School of Mathematical Sciences Peking University Beijing100871 China University of Chinese Academy of Sciences Institute of Computing Technology of Chinese Academy of Sciences Beijing100190 China Department of Mathematics and by courtesy Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

In crowdsourced preference aggregation, it is often assumed that all the annotators are subject to a common preference or social utility function which generates their comparison behaviors in experiments. However, in reality annotators are subject to variations due to multi-criteria, abnormal, or a mixture of such behaviors. In this paper, we propose a parsimonious mixed-effects model, which takes into account both the fixed effect that the majority of annotators follows a common linear utility model, and the random effect that some annotators might deviate from the common significantly and exhibit strongly personalized preferences. The key algorithm in this paper establishes a dynamic path from the social utility to individual variations, with different levels of sparsity on personalization. The algorithm is based on the Linearized Bregman Iterations, which leads to easy parallel implementations to meet the need of large-scale data analysis. In this unified framework, three kinds of random utility models are presented, including the basic linear model with L2 loss, Bradley-Terry model, and Thurstone-Mosteller model. The validity of these multi-level models are supported by experiments with both simulated and real-world datasets, which shows that the parsimonious multi-level models exhibit improvements in both interpretability and predictive precision compared with traditional HodgeRank. Copyright © 2018, The Authors. All rights reserved.

关键词： Crowdsourcing

来源：评论

学校读者我要写书评

暂无评论

Understanding of collective atom phase control in modified photon echoes for a near perfect, storage time extended quantum memory

arXiv

引用

arXiv 2017年

作者： Rahmatullah Ham, B.S. Center for Photon Information Processing School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju61005 Korea Republic of Quantum Optics Lab. Department of Physics COMSATS Institute of Information Technology Islamabad Pakistan

A near perfect, storage time-extended photon echo-based quantum memory protocol has been analyzed by solving the Maxwell-Bloch equations for a backward scheme in a three-level system. The backward photon echo scheme is combined with a controlled coherence conversion process via control Rabi flopping to a third state, where the control Rabi flopping collectively shifts the phase of the ensemble coherence. The propagation direction of photon echoes is coherently determined by the phase matching condition between the data (quantum) and the control (classical) pulses. Herein we discuss the classical controllability of a quantum state for both phase and propagation direction by manipulating the control pulses in both single and double rephasing photon echo schemes of a three-level system. Compared with their well-understood use for two-level photon echoes, the Maxwell-Bloch equations to a three-level system have a critical limitation regarding the phase change when interacted with an arbitrary control pulse area. Copyright © 2017, The Authors. All rights reserved.

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

Abstracts

引用

JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：