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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Timothy K. Horiuchi Matthew Cheely Electrical and Computer Engineering Department Institute for Systems Research Neuroscience and Cognitive Science Program University of Maryland College park MD USA Neuroscience and Cognitive Science Program University of Maryland College park MD USA

Echolocating bats have long demonstrated the potential for air-coupled sonar to guide agile navigation through complex 3D environments. While air-coupled sonar has been extensively used in mobile ground robotics and a considerable amount of the bat's auditory system has been studied, little work has been done to understand how the neural circuitry of the bat can integrate echoes into a coherent, behaving system. This paper addresses the unique characteristics of bat echolocation and how they impact the design of a neuromorphic VLSI-based echolocation system. By constructing a system to solve bat-specific sensorimotor tasks the authors have encountered a number of interesting issues and questions that commonly face neuromorphic VLSI designers. Successes, problematic issues, and future directions are discussed

关键词： Neuromorphics Very large scale integration Auditory system Neurons Sonar navigation Mobile robots Frequency Delay estimation neuroscience Cognitive science

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Functional mechanisms of motor skill acquisition

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BMC neuroscience 2007年第2期8卷 1-2页

作者： Ashvin Shah Andrew G Barto Neuroscience and Behavior Program University of Massachusetts Amherst Amherst MA 01003 USA Department of Computer Science University of Massachusetts Amherst Amherst MA 01003 USA

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Epileptic seizure detection

Epileptic seizure detection

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作者： Schuyler, Ronald White, Andrew Staley, Kevin Cios, Krzysztof J. Computational Bioscience Ph.D. Program UCDHSC United States University of Colorado United States American Epilepsy Society Society for Neuroscience United States Department of Neurology Massachusetts General Hospital Harvard Medical School United States Staley Lab. United States University of Colorado at Denver Health Sciences Center United States University of Colorado Bioenergetics Institute United States Data Mining and Bioinformatics Laboratory Turkey Polish Academy of Arts and Sciences Poland Dept. of Computer Science and Engineering University of Colorado at Denver Health Sciences Center P.O. Box 173364 Denver CO 80217-3364 United States

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An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed

An Integrated Model of Top-Down and Bottom-Up Attention for ...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： V. Navalpakkam L. Itti Department of Computer Science Neuroscience Graduate Program University of Southern California USA

Integration of goal-driven, top-down attention and image-driven, bottom-up attention is crucial for visual search. Yet, previous research has mostly focused on models that are purely top-down or bottom-up. Here, we propose a new model that combines both. The bottom-up component computes the visual salience of scene locations in different feature maps extracted at multiple spatial scales. The topdown component uses accumulated statistical knowledge of the visual features of the desired search target and background clutter, to optimally tune the bottom-up maps such that target detection speed is maximized. Testing on 750 artificial and natural scenes shows that the model’s predictions are consistent with a large body of available literature on human psychophysics of visual search. These results suggest that our model may provide good approximation of how humans combine bottom-up and top-down cues such as to optimize target detection speed.

关键词： Object detection Layout Biological system modeling Humans Face detection Acceleration Robots Navigation Surveillance computer science

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A neural model for sonar-based navigation in obstacle fields

A neural model for sonar-based navigation in obstacle fields

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： T.K. Horiuchi Institute for Systems Research & The Neuroscience and Cognitive Science Program Electrical and Computer Engineering Department University of Maryland College Park MD USA

The rapid control of sonar-guided vehicles through obstacle fields has been a goal of robotics for decades. How sensory data is represented strongly affects how obstacles and goal information can be combined to select a direction of travel. While typical approaches combine attractive and repulsive effects to directly determine steering, we are investigating an algorithm that evaluates multiple directions simultaneously followed by a winner-take-all (WTA) function which then guides steering. In this paper we describe a neuromorphic VLSI implementation of this algorithm using the inherent echo delay to create a range-dependent gain in a 'race-to-first-spike' neural WTA circuit. The chip was fabricated in a commercially-available 0.5 mum CMOS process and in this paper we present preliminary test results

关键词： Sonar navigation Robot sensing systems Neurons Automotive engineering neuroscience Cognitive science Educational institutions Control systems Vehicles Cognitive robotics

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Fast forward projection and backward projection algorithm using SIMD

Fast forward projection and backward projection algorithm us...

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IEEE Symposium on Nuclear science (NSS/MIC)

作者： I. K. Hong S. T. Chung H. K. Kim Y. B. Kim Y. D. Son Z. H. Cho Department of Computer Engineering Korea Polytechnic University Gyeonggi South Korea Neuroscience Research Institute Gachon University of Medicine and Science Incheon South Korea Biomedical Engineering Program University of California Irvine CA USA Radiological Sciences & Psychiatry and Human Behavior University of California Irvine CA USA

Recent developments in PET scanners such as the HRRT (High Resolution Research Tomograph) developed by Siemens greatly enhanced their resolution as well as sensitivity, but they increased coincidence lines of response more than 4.5 times 10 generated by as many nuclear detectors as 120,000. This formidable amount of data poses a real problem in the image reconstruction and its applications. It also has been the major bottleneck in further developments of the higher resolution PET scanners. To remedy this problem in the image reconstruction, we developed a new algorithm based on the SIMD (Single Instruction Multiple Data) technique incorporated with the symmetry properties of the projection and backprojection processes, especially in the 3D OSEM algorithm. We refer to this technique as the SSP (Symmetry and SIMD based Projection-backprojection) algorithm. As a demonstration, the algorithm was applied to the OSEM (Ordered Subset Expectation Maximization) 3D algorithm with HRRT data and it effectively reduced the total image reconstruction time to 80 folds.

关键词： Projection algorithms Image reconstruction Positron emission tomography neuroscience Biomedical imaging Detectors Iterative methods Biomedical engineering Nuclear and plasma sciences Nuclear power generation

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Distributed biologically based real time tracking in the absence of prior target information

Distributed biologically based real time tracking in the abs...

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Intelligent Robots and computer Vision XXIII: Algorithms, Techniques, and Active Vision

作者： Mundhenk, T.Nathan Everist, Jacob Landauer, Chris Itti, Laurent Bellman, Kirstie Computer Science Department Henry Salvatori Computer Science Center University of Southern California Los Angeles CA 90089-0781 Neuroscience Program Hedco Neuroscience Building University of Southern California Los Angeles CA 90089-2520 Aerospace Integration Science Center Aerospace Corporation 2350 E. El Segundo Blvd El Segundo CA 90245-4691 University of Southern California HNB 10 3641 Watt Way Los Angeles Ca 90089-2520

We are developing a distributed system for the tracking of people and objects in complex scenes and environments using biologically based algorithms. An important component of such a system is its ability to track targets from multiple cameras at multiple viewpoints. As such, our system must be able to extract and analyze the features of targets in a manner that is sufficiently invariant of viewpoints, so that they can share information about targets, for purposes such as tracking. Since biological organisms are able to describe targets to one another from very different visual perspectives, by discovering the mechanisms by which they understand objects, it is hoped such abilities can be imparted on a system of distributed agents with many camera viewpoints. Our current methodology draws from work on saliency and center surround competition among visual components that allows for real time location of targets without the need for prior information about the targets visual features. For instance, gestalt principles of color opponencies, continuity and motion form a basis to locate targets in a logical manner. From this, targets can be located and tracked relatively reliably for short periods. Features can then be extracted from salient targets allowing for a signature to be stored which describes the basic visual features of a target. This signature can then be used to share target information with other cameras, at other viewpoints, or may be used to create the prior information needed for other types of trackers. Here we discuss such a system, which, without the need for prior target feature information, extracts salient features from a scene, binds them and uses the bound features as a set for understanding trackable objects.

关键词： Tracking (position)

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Camera localization methods for intelligent room systems using RF techniques

Camera localization methods for intelligent room systems usi...

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Intellignt Robots and computer Vision XXII: Algorithms, Techniques, and Active Vision

作者： Natarajan, Pradeep Mundhenk, T. Nathan Bellman, K. Itti, L. Arbib, M. Computer Science Department Henri Salvatori Comp. Science Center University of Southern California Los Angeles CA 90089-0781 Neuroscience Program Hedco Neuroscience Building University of Southern California Los Angeles CA 90089-2520 Aerospace Integration Science Center Aerospace Corporation 2350 E. El Segundo Blvd. El Segundo CA 90245-4691

One of the important components of a multi sensor "intelligent" room, which can observe, track and react to its occupants, is a multi camera system. This system involves the development of algorithms that enable a set of cameras to communicate and cooperate with each other effectively so that they can monitor the events happening in the room. To achieve this, the cameras typically must first build a map of their relative locations. In this paper, we discuss a novel RF based technique for estimating distances between cameras. The algorithm proposed for RF can estimate distances with relatively good accuracy even in the presence of random noise.

关键词： Artificial intelligence

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A summating, exponentially-decaying CMOS synapse for spiking neural systems

A summating, exponentially-decaying CMOS synapse for spiking...

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17th Annual Conference on Neural Information Processing Systems, NIPS 2003

作者： Shi, Rock Z. Horiuchi, Timothy Electrical and Computer Engineering Department University of Maryland College Park MD 20742 United States Institute for Systems Research University of Maryland College Park MD 20742 United States Neuroscience and Cognitive Science Program University of Maryland College Park MD 20742 United States

ISBN: (纸本)0262201526

Synapses are a critical element of biologically-realistic, spike-based neural computation, serving the role of communication, computation, and modification. Many different circuit implementations of synapse function exist with different computational goals in mind. In this paper we describe a new CMOS synapse design that separately controls quiescent leak current, synaptic gain, and time-constant of decay. This circuit implements part of a commonly-used kinetic model of synaptic conductance. We show a theoretical analysis and experimental data for prototypes fabricated in a commercially-available 1.5μm CMOS process.

关键词： CMOS integrated circuits

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Effects of Spectro-Temporal Asynchrony in Auditory and Auditory-Visual Speech Processing

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Seminars in Hearing 2004年第3期25卷 241-255页

作者： Ken W. Grant Steven Greenberg David Poeppel Virginie van Wassenhove 1 Auditory-Visual Speech Recognition Laboratory Walter Reed Army Medical Center Army Audiology and Speech Center Washington District of Columbia 2 International Computer Speech Institute Berkeley California 3 Cognitive Neuroscience of Language Laboratory Neuroscience and Cognitive Science Program (NACS) Department of Biology and Department of Linguistics University of Maryland College Park Maryland

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