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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Optimal signal processing method in UWB radar for hidden human detection

Optimal signal processing method in UWB radar for hidden hum...

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作者： Karamzadeh, Saeid Kartal, Mesut Kent, Sedef Ashtiyani, A. Abed Informatics Institute Department of Advanced Technology Satellite Communication and Remote Sensing Program Istanbul Technical University Turkey Department of Electronics and Communications Faculty of Electrical and Electronic Engineering Istanbul Technical University Turkey Faculty of Electric and Computer University of Tabriz Iran

Today, human detection and tracking is important challenge for many aims. In this study, we are used Ultra Wide Band (UWB) radar for human respiratory detection behind a wall. The modulated system to get the breathing signal is introduced. The results of simulation part of the established system are presented. Suitable antenna for using as a transmitter and receiver is being discussed. Different signal processing methods are debated and optimal method is introduced for various environments. © VDE VERLAG GMBH · Berlin · Offenbach, Germany.

关键词： Antennas

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Image-based food volume estimation

Image-based food volume estimation

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5th International Workshop on Multimedia for Cooking and Eating Activities, CEA 2013

作者： Xu, Chang He, Ye Parra, Albert Delp, Edward Khanna, Nitin Boushey, Carol School of Electrical and Computer Engineering Purdue University West Lafayette IN United States Department of Electronics and Communication Engineering Graphic Era University Dehradun India Cancer Epidemiology Program University of Hawaii Cancer Center Honolulu HI United States

ISBN: (纸本)9781450323925

In this paper, we propose an extension to our previous work on food portion size estimation using a single image and a multi-view volume estimation method. The single-view technique estimates food volume by using prior information (segmentation and food labels) generated from food identification methods we described earlier. For multi-view volume estimation, we use "Shape from Silhouettes" to estimate the food portion size. The experimental results of our volume estimation methods demonstrate our results with respect to accuracy and reliability. © Copyright 2013 ACM.

关键词： Image reconstruction

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Image segmentation for image-based dietary assessment: A comparative study

Image segmentation for image-based dietary assessment: A com...

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International Symposium on Signals, Circuits and Systems (ISSCS)

作者： Y. He N. Khanna C. J. Boushey E. J. Delp School of Electrical and Computer Engineering Purdue University Department of Electronics and Communication Engineering Graphic Era University Cancer Epidemiology Program University of Hawaii Cancer Center

There is a health crisis in the US related to diet that is further exacerbated by our aging population and sedentary lifestyles. Six of the ten leading causes of death in the United States can be directly linked to diet. Dietary assessment, the process of determining what someone eats during the course of a day, is essential for understanding the link between diet and health. We are developing imaging based tools to automatically obtain accurate estimates of what foods a user consumes. Accurate food segmentation is essential for identifying food items and estimating food portion sizes. In this paper, we present a quantitative evaluation of automatic image segmentation methods for food image analysis used for dietary assessment. The experiments indicate that local variation is more suitable for food image segmentation in general dietary assessment studies where the food images acquired have complex background.

关键词： Image segmentation Active contours Educational institutions Mobile communication Equations Image edge detection Conferences

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Food image analysis: Segmentation, identification and weight estimation

Food image analysis: Segmentation, identification and weight...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Ye He Chang Xu Nitin Khanna Carol J. Boushey Edward J. Delp School of Electrical and Computer Engineering Purdue University USA Department of Electronics and Communication Engineering Graphic Era University India Cancer Epidemiology Program University of Hawaii USA

ISBN: (纸本)9781479900145

We are developing a dietary assessment system that records daily food intake through the use of food images taken at a meal. The food images are then analyzed to extract the nutrient content in the food. In this paper, we describe the image analysis tools to determine the regions where a particular food is located (image segmentation), identify the food type (feature classification) and estimate the weight of the food item (weight estimation). An image segmentation and classification system is proposed to improve the food segmentation and identification accuracy. We then estimate the weight of food to extract the nutrient content from a single image using a shape template for foods with regular shapes and area-based weight estimation for foods with irregular shapes.

关键词： Image segmentation Image color analysis Shape Estimation Accuracy Cameras Three-dimensional displays

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MODEL-BASED FOOD VOLUME ESTIMATION USING 3D POSE

MODEL-BASED FOOD VOLUME ESTIMATION USING 3D POSE

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IEEE International Conference on Image Processing

作者： Chang Xu Ye He Nitin Khanna Carol J. Boushey Edward J. Delp School of Electrical and Computer Engineering Purdue University Department of Electronics and Communication Engineering Graphic Era University Dehradun India Cancer Epidemiology Program University of Hawaii Cancer Center

ISBN: (纸本)9781479923427

We are developing a dietary assessment system to automatically identify and quantify foods and beverages consumed by analyzing meal images captured with a mobile device. After food items are segmented and identified, accurately estimating the volume of the food in the image is important for determining the nutrient content of the food. In this paper, we proposed a novel food portion size estimation method for rigid food items using a single image. First, we create a 3D graphical model during the training step using 3D reconstruction from multiple views. Then, for each food image, we determine the translation and elevation parameters of each of the food items, which are relative to the camera coordinate through camera calibration. Using these geometric parameters we project the pre-built 3D model of each food item back to the image plane. Subsequently, the remaining degrees-of-freedom (DOF) for the final pose is estimated by image similarity measure. The experimental results of our volume estimation method for four food categories validate the accuracy and reliability of our model-based approach.

关键词： dietary assessment 3D reconstruction 3D model rendering image segmentation pose estimation three-dimensional displays Food pose estimation image segmentation images Posing Imagery (Psychotherapy) image plane camera calibration Image Three Dimensions geometric parameter

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CONTEXT BASED FOOD IMAGE ANALYSIS

CONTEXT BASED FOOD IMAGE ANALYSIS

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IEEE International Conference on Image Processing

作者： Ye He Chang Xu Nitin Khanna Carol J. Boushey Edward J. Delp School of Electrical and Computer Engineering Purdue University Department of Electronics and Communication Engineering Graphic Era University Dehradun India Cancer Epidemiology Program University of Hawaii Cancer Center

ISBN: (纸本)9781479923427

We are developing a dietary assessment system that records daily food intake through the use of food images. Recognizing food in an image is difficult due to large visual variance with respect to eating or preparation conditions. This task becomes even more challenging when different foods have similar visual appearance. In this paper we propose to incorporate two types of contextual dietary information, food co-occurrence patterns and personalized learning models, in food image analysis to reduce ambiguity in food visual appearance and improve food recognition accuracy. We evaluate our model on 1453 food images acquired by 45 participants in natural eating conditions. The result shows that incorporating contextual dietary information improves the food categorization accuracy by about 10%.

关键词： Dietary Assessment Contextual Information Food Recognition Image Segmentation Fodder Food image segmentation Food Intake image analysis images

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Multicharged optical vortices induced in a dissipative atomic vapor system

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Physical Review A 2013年第1期88卷 013847-013847页

作者： Yiqi Zhang (张贻齐) Milivoj Belić Zhenkun Wu (吴振坤) Chenzhi Yuan (袁晨智) Ruimin Wang (王瑞敏) Keqing Lu (卢克清) Yanpeng Zhang (张彦鹏) Key Laboratory for Physical Electronics and Devices of the Ministry of Education & Shaanxi Key Lab of Information Photonic Technique Xi'an Jiaotong University Xi'an 710049 China Science Program Texas A&M University at Qatar P.O. Box 23874 Doha Qatar School of Information and Communication Engineering Tianjin Polytechnic University Tianjin 300160 China

We investigate numerically the dynamics of optical vortex beams carrying different topological charges, launched in a dissipative three-level ladder-type nonlinear atomic vapor. We impose the electromagnetically induced transparency (EIT) condition on the medium. Linear, cubic, and quintic susceptibilities, considered simultaneously with the dressing effect, are included in the analysis. Generally, the beams slowly expand during propagation and new vortices are induced, commonly appearing in oppositely charged pairs. We demonstrate that not only the form and the topological charge of the incident beam but also its growing size in the medium greatly affect the formation and evolution of vortices. We formulate common rules for finding the number of induced vortices and the corresponding rotation directions, stemming from the initial conditions of various incident beams, as well as from the dynamical aspects of their propagation. The net topological charge of the vortex is conserved during propagation, as it should be, but the total number of charges is not necessarily the same as the initial number, because of the complex nature of the system. When the EIT condition is lifted, an enhancement region of beam dynamics is reached, in which the dynamics and the expansion of the beam greatly accelerate. In the end, we discuss the liquid-like behavior of light evolution in this dissipative system and propose a potential experimental scheme for observing such a behavior.

关键词： MULTIPLY charged ions OPTICAL vortices ENERGY dissipation VAPORS ELECTROMAGNETISM OBSERVATION (Scientific method)

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Amplitude and frequency modulation behaviours of cellular neural networks

Amplitude and frequency modulation behaviours of cellular ne...

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International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2012

作者： Tander, Baran Özmen, Atilla Kadir Has University Vocational School of Technical Sciences Communication Electronics Program 34590 Selimpaşa Istanbul Turkey Kadir Has University School of Engineering Electronics Engineering Department 34083 Cibali Istanbul Turkey

ISBN: (纸本)9781467314466

As is well known, Amplitude Modulation (AM) and Frequency Modulation (FM) are the most popular modulation techniques in communications [1]. Classically, they are designed as individual systems at transmitters;however in this study, it is shown that, both can be realized under a single architecture, specifically on a Cellular Neural Network with an opposite sign template (CNN-OST). First, the CNN-OST is introduced and then, AM and FM behaviours of this structure are explained. Simulations are carried out where satisfactory results are found and finaly, the advantages and drawbacks of the proposed system are discussed. © 2012 IEEE.

关键词： Frequency modulation

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