Conferences related to Neurons

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2018 17th International Conference on Information Technology Based Higher Education and Training (ITHET)

The convergence of current technologies provides the infrastructure for transmitting and storing information faster and cheaper. For information to be used in gaining knowledge, however, environments for collecting, storing, disseminating, sharing and constructing knowledge are needed. Such environments, knowledge media, brings together telecommunication, computer and networking technologies, learning theories and cognitive sciences to form meaningful environments that provides for a variety of learner needs. ITHET 2018 will continue with the traditional themes of previous events. However, our special theme for this year is a fundamental one. We have previously had MOOCs as our special theme, but now they are just infrastructure. Even “Blended Learning” is what we all do anyway. In a time of the unprecedented access to knowledge through IT, it is time for us to revisit the fundamental purpose of our educational system. It is certainly not about knowledge anymore.


2018 26th Signal Processing and Communications Applications Conference (SIU)

The general scope of the conference ranges from signal and image processing to telecommunication, and applications of signal processing methods in biomedical and communication problems.

  • 2017 25th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing and Communication Applications (SIU) conference is the most prominent scientific meeting on signal processing in Turkey bringing together researchers working in signal processing and communication fields. Topics include but are not limited to the areas of research listed in the keywords.

  • 2016 24th Signal Processing and Communication Application Conference (SIU)

    Signal Processing Theory, Statistical Signal Processing, Nonlinear Signal Processing, Adaptive Signal Processing, Array and Multichannel Signal Processing, Signal Processing for Sensor Networks, Time-Frequency Analysis, Speech / Voice Processing and Recognition, Computer Vision, Pattern Recognition, Machine Learning for Signal Processing, Human-Machine Interaction, Brain-Computer Interaction, Signal-Image Acquisition and Generation, image Processing, video Processing, Image Printing and Presentation, Image / Video / Audio browsing and retrieval, Image / Video / Audio Watermarking, Multimedia Signal Processing, Biomedical Signal Processing and Image Processing, Bioinformatics, Biometric Signal-Image Processing and Recognition, Signal Processing for Security and Defense, Signal and Image Processing for Remote Sensing, Signal Processing Hardware, Signal Processing Education, Radar Signal Processing, Communication Theory, Communication Networks, Wireless Communications

  • 2015 23th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing Theory Statistical Signal Processing Nonlinear Signal Processing Adaptive Signal Processing Array and Multichannel Signal Processing Signal Processing for Sensor Networks Time-Frequency Analysis Speech / Voice Processing and Recognition Computer Vision Pattern Recognition Machine Learning for Signal Processing Human-Machine Interaction Brain-Computer Interaction Signal-Image Acquisition and Generation image Processing video Processing Image Printing and Presentation Image / Video / Audio browsing and retrieval Image / Video / Audio Watermarking Multimedia Signal Processing Biomedical Signal Processing and Image Processing Bioinformatics Biometric Signal-Image Processing and Recognition Signal Processing for Security and Defense Signal and Image Processing for Remote Sensing Signal Processing Hardware Signal Processing Education Radar Signal Processing Communication Theory Communication Networks Wireless Communications

  • 2014 22nd Signal Processing and Communications Applications Conference (SIU)

    SIU will be held in Trabzon, Turkey at the Karadeniz Technical University Convention and Exhibition Centre on April 23, 2014. SIU is the largest and most comprehensive technical conference focused on signal processing and its applications in Turkey. Last year there were 500 hundred participants. The conference will feature renowned speakers, tutorials, and thematic workshops. Topics include but are not limited to: Signal Procesing, Image Processing, Communication, Computer Vision, Machine Learning, Biomedical Signal Processing,

  • 2013 21st Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2012 20th Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2011 19th Signal Processing and Communications Applications Conference (SIU)

    Conference will bring together academia and industry professionals as well as students and researchers to present and discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. The Conference will also include invited lectures, tutorials and special sessions.

  • 2010 IEEE 18th Signal Processing and Communications Applications Conference (SIU)

    S1.Theory of Signal-Processing S2.Statistical Signal-Processing S3.Multimedia Signal-Processing S4.Biomedical Signal-Processing S5.Sensor Networks S6.Multirate Signal-Processing S7.Pattern Recognition S8.Computer Vision S9.Adaptive Filters S10.Image/Video/Speech Browsing, Retrieval S11.Speech/Audio Coding S12.Speech Processing S13.Human-Machine Interfaces S14.Surveillance Signal Processing S15.Bioinformatics S16.Self-Learning S17.Signal-Processing Education S18.Signal-Processing Systems S1

  • 2009 IEEE 17th Signal Processing and Communications Applications Conference (SIU)

    The scope of the conference is to cover recent topics in theory and applications of Signal Processing and Communications.

  • 2008 IEEE 16th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing, Image Processing, Speech Processing, Pattern Recognition, Human Computer Interaction, Communication, Video and Speech indexing, Computer Vision, Biomedical Signal Processing

  • 2007 IEEE 15th Signal Processing and Communications Applications (SIU)

  • 2006 IEEE 14th Signal Processing and Communications Applications (SIU)

  • 2005 IEEE 13th Signal Processing and Communications Applications (SIU)

  • 2004 IEEE 12th Signal Processing and Communications Applications (SIU)


2018 European Conference on Antennas and Propagation (EuCAP)

Antennas & related topics e.g. theoretical methods, systems, wideband, multiband, UWBPropagation & related topics e.g. modelling/simulation, HF, body-area, urbanAntenna & RCS measurement techniques


2018 IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA)

The colloquium will provide an excellent platform for knowledge exchange between researchers, scientists, academicians and engineers working in the areas of automation, process, scientific research and analysis. This event calls for local and international participation.Field of Interest:


2018 IEEE 16th International Conference on Industrial Informatics (INDIN)

The aim of INDIN´18 is to bring together researchers and practitioners from industry and academia and provide them with a platform to report and discuss recent developments, deployments, technology trends and research results, as well as initiatives related to industrial informatics and their application.


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Periodicals related to Neurons

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems I: Regular Papers, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


Circuits and Systems II: Express Briefs, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


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Most published Xplore authors for Neurons

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Xplore Articles related to Neurons

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GLOSSARY

[{u'author_order': 1, u'affiliation': u'Dublin Institute of Technology', u'full_name': u'John D. Kelleher'}, {u'author_order': 2, u'affiliation': u'Dublin Institute of Technology', u'full_name': u'Brendan Tierney'}] Data Science, None

None


Glossary

[{u'author_order': 1, u'affiliation': u'Salk Institute for Biological Studies', u'full_name': u'Terrence J. Sejnowski'}] The Deep Learning Revolution, None

None


I Intelligence Reimagined

[{u'author_order': 1, u'affiliation': u'Salk Institute for Biological Studies', u'full_name': u'Terrence J. Sejnowski'}] The Deep Learning Revolution, None

None


RBF networks for density estimation

[{u'author_order': 1, u'affiliation': u'Department of Electronic & Electrical Engineering, University of Surrey, Guildford, Surrey GU2 5XH, United Kingdom', u'full_name': u'Lucia Sardo'}, {u'author_order': 2, u'affiliation': u'Department of Electronic & Electrical Engineering, University of Surrey, Guildford, Surrey GU2 5XH, United Kingdom', u'full_name': u'Josef Kittler'}] 1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

A non-parametric probability density function (pdf) estimation technique is presented. The estimation consists in approximating the unknown pdf by a network of Gaussian Radial Basis Functions (GRBFs). Complexity analysis is introduced in order to select the optimal number of GRBFs. Results obtained on real data show the potentiality of this technique.


16 Consciousness

[{u'author_order': 1, u'affiliation': u'Salk Institute for Biological Studies', u'full_name': u'Terrence J. Sejnowski'}] The Deep Learning Revolution, None

When his mother asked young Francis Crick what scientific problems he wanted to pursue in life, he told her there were only two that interested him: the mystery of life and the mystery of consciousness.1Crick clearly had a keen sense for what is important, but he may not have appreciated the difficulty of these problems. Little did his mother know ...


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eLearning

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IEEE-USA E-Books

  • GLOSSARY

    None

  • Glossary

    None

  • I Intelligence Reimagined

    None

  • 16 Consciousness

    When his mother asked young Francis Crick what scientific problems he wanted to pursue in life, he told her there were only two that interested him: the mystery of life and the mystery of consciousness.1Crick clearly had a keen sense for what is important, but he may not have appreciated the difficulty of these problems. Little did his mother know that, decades later in 1953, her son and James Watson would discover the structure of DNA—the loose thread that would eventually unravel one of life's great mysteries. But Crick (figure 16.1) was not content with this achievement.

  • 11 NEURAL NETWORKS THAT CAN HEAR, SPEAK, AND REMEMBER

    We've spent most of the past few chapters looking at how deep neural networks are able to recognize objects in images. I've focused on these networks largely because many of the machines in this book use vision in some form to perceive the world around them. But what if we wanted our machines to have other ways to interact with the world—to generate English sentences, or to understand human speech, for example? Would convolutional networks prove useful for this as well? Are there other neural network “primitives” that would be helpful? Popping up a level, does it even make sense to use neural networks for tasks like understanding speech?

  • Recurrent Neural Networks

    This chapter considers a class of neural networks that have a recurrent structure, including Grossberg network, Hopfield network, and cellular neural networks. The Hopfield network is a form of recurrent artificial neural network invented by John Hopfield in 1982. It consists of a set of neurons and a corresponding set of unit time delays, formatting a multiple-loop feedback system. There are three components to the Grossberg network: Layer 1, Layer 2, and the adaptive weights. Layer 1 is a rough model of the operation of the retina, while Layer 2 represents the visual cortex. Cellular neural networks contain linear and nonlinear circuit elements, which typically are linear capacitors, linear resistors, linear and nonlinear controlled sources, and independent sources. The chapter also describes the mathematical model of a nonlinear dynamic system, and discusses some of the important issues involved in neurodynamics.

  • 8 HOW TO BEAT ATARI GAMES BY USING NEURAL NETWORKS

    Even before Google acquired DeepMind in 2014, word about this new research company was spreading quietly. At a machine learning conference in late 2012, for instance, DeepMind had been competing aggressively with companies like Facebook and Google to recruit members of the machine learning community.1And conference attendees learned that the founder of this mysterious company was Demis Hassabis, a quiet, brilliant, and ambitious neuroscientist.

  • Surface EMG Decomposition

    This chapter provides an overview of surface EMG decomposition techniques, along with their basic assumptions, properties, and limitations. Surface electrodes measure the electrical activity of several nearby muscle fibers that are active during a muscle contraction. The electrical activity of each fiber can be described by a single fiber action potential (SFAP) that propagates from the neuromuscular junction towards the tendons. There is large diversity of decomposition techniques that can roughly be categorized either as template matching or latent component analysis (blind source separation) approaches. Decomposition of surface EMG is a powerful tool enabling noninvasive insight not only into muscle control strategies, but also into peripheral muscle properties. It provides unambiguous information on physiological parameters of individual motor units that can easily be interpreted. The identification of motor units (MUs) discharge patterns from surface EMG signals, acquired during dynamic muscle contractions, needs to be addressed.

  • 9 ARTIFICIAL NEURAL NETWORKS' VIEW OF THE WORLD

    In 2016, a Bloomberg News reporter wrote that several startup companies had begun offering intelligent “chatbots” as personal assistants.1One of these chatbots, named Amy Ingram, was marketed by her company as “a personal assistant who schedules meetings for you.” You simply needed to “cc” Amy to an email thread for her to do her magic. Users of the service liked Amy's “humanlike tone” and “eloquent manners.” One user said she was “actually better than a human for this task.” Some men even asked her out on dates.

  • 5 Insights from the Visual System

    One of my earliest memories, before going to kindergarten, was peering over pieces of a jigsaw puzzle and matching them using shape, color, and context as cues. My parents would amaze their friends at parties by how quickly their toddler son could put jigsaw puzzles together. I did not know it then, but my brain was doing what brains do best—solving problems with pattern recognition. Science is filled with problems that are like puzzles with missing pieces and vague hints to the underlying picture. How brains solve problems is the ultimate puzzle.



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