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检索条件"机构=Computation and Neural Systems Program California"
92 条 记 录,以下是71-80 订阅
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Automated event detection in underwater video
Automated event detection in underwater video
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OCEANS
作者: D.R. Edgington K.A. Salamy M. Risi R.E. Sherlock D. Walther Christof Koch Monterey Bay Aquarium Research Institute Moss Landing CA USA Computation and Neural Systems Program California Institute of Technology Pasadena CA USA
We present an attentional selection system for processing video streams from remotely operated underwater vehicles (ROVs). The system identifies potentially interesting visual events spanning multiple frames based on ... 详细信息
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Adaptation of current signals with floating-gate circuits
Adaptation of current signals with floating-gate circuits
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作者: Pesavento, Alberto Horiuchi, Timothy Diorio, Chris Koch, Christof Department of Electrical Engineering California Institute of Technology Pasadena CA 91125 United States Department of Electrical and Computer Engineering University of Maryland College Park MD 20742 United States Department of Computer Science and Engineering University of Washington Seattle WA 98195-2350 United States Computation and Neural Systems Program California Institute of Technology Pasadena CA 91125 United States
In this paper we present a new, adaptive spatial-derivative circuit for CMOS image sensors. The circuit removes its offset as a natural part of its operation using a combination of electron tunneling and hot-electron ... 详细信息
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Generalized smoothing networks in early vision
Generalized smoothing networks in early vision
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: S.-C. Liu J.G. Harris Rockwell Science Center Inc. Thousand Oaks CA USA California Institute of Technology 216-76 Computation and Neural Systems Program Pasadena CA USA
Generalized smoothing networks have been developed which enforce smoothness constraints for any arbitrary level of derivative of the input data. Furthermore, discontinuities of any order of derivative can be detected ... 详细信息
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Fast learning with predictive forward models  91
Fast learning with predictive forward models
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Proceedings of the 5th International Conference on neural Information Processing systems
作者: Carlos Brody Computation and Neural Systems Program California Institute of Technology Pasadena CA and Dept. of Computer Science IIMAS UNAM México D.F. México
A method for transforming performance evaluation signals distal both in space and time into proximal signals usable by supervised learning algorithms, presented in [Jordan & Jacobs 90], is examined. A simple obser...
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Feedforward architectures driven by inhibitory interactions
arXiv
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arXiv 2017年
作者: Billeh, Yazan N. Schaub, Michael T. Computation and Neural Systems Program California Institute of Technology Université Catholique de Louvain Massachusetts Institute of Technology Institute for Data Systems and Society Massachusetts Institute of Technology Department of Engineering Science University of Oxford
Directed information transmission is paramount for many social, physical, and biological sys- tems. For neural systems, scientists have studied this problem under the paradigm of feedforward networks for decades. In m... 详细信息
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Computing optical flow in resistive networks and in the primate visual system
Computing optical flow in resistive networks and in the prim...
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Workshop on Visual Motion
作者: C. Koch H.T. Wang B. Mathur A. Hsu H. Suarez Computation and Neural Systems Program Divisions of Biology and Engineering and Applied Sciences California Institute of Technology Pasadena CA USA Science Center Rockwell International Thousand Oaks CA USA
It is shown how the well-known algorithm of B. Horn and B.C. Schunk (1981) for computing optical flow, based on minimizing a quadratic functional using a relaxation scheme, maps onto two different kinds of massive par... 详细信息
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Incorporating contextual information in white blood cell identification  97
Incorporating contextual information in white blood cell ide...
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Proceedings of the 11th International Conference on neural Information Processing systems
作者: Xubo Song Yaser Abu-Mostafa Joseph Sill Department of Electrical Engineering California Institute of Technology Pasadena CA Dept. of Electrical Engineering and Dept. of Computer Science California Institute of Technology Pasadena CA Computation and Neural Systems Program California Institute of Technology Pasadena CA
In this paper we propose a technique to incorporate contextual information into object classification. In the real world there are cases where the identity of an object is ambiguous due to the noise in the measurement...
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Modeling the modulatory effect of attention on human spatial vision  01
Modeling the modulatory effect of attention on human spatial...
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Proceedings of the 14th International Conference on neural Information Processing systems: Natural and Synthetic
作者: Laurent Itti Jochen Braun Christof Koch Computer Science Department University of Southern California Los Angeles CA Institute of Neuroscience and School of Computing University of Plymouth Plymouth Devon U.K. Computation and Neural Systems Program California Institute of Technology Pasadena CA
We present new simulation results, in which a computational model of interacting visual neurons simultaneously predicts the modulation of spatial vision thresholds by focal visual attention, for five dual-task human p...
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An adaptive multi-scale approach for estimating optical flow: computational theory and physiological implementation
An adaptive multi-scale approach for estimating optical flow...
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Workshop on Visual Motion
作者: C. Koch H.T. Wang R. Battiti B. Mathur C. Ziomkowski Computation and Neural Systems Program California Institute of Technology Pasadena CA USA Science Center Rockwell International Thousand Oaks CA USA Dipartimento di Fisica Universita di Genova Genoa Italy
The accuracy of optical flow estimation depends on the spatio-temporal discretization used in the computation. The authors propose an adaptive multiscale method, where the discretization scale is chosen locally accord... 详细信息
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Viewpoints: Approaches to defining and investigating fear
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NATURE NEUROSCIENCE 2019年 第8期22卷 1205-1216页
作者: Mobbs, Dean Adolphs, Ralph Fanselow, Michael S. Barrett, Lisa Feldman LeDoux, Joseph E. Ressler, Kerry Tye, Kay M. Department of Humanities and Social Sciences and Computation and Neural Systems Program California Institute of Technology Pasadena California USA Departments of Psychology and Psychiatry and Biobehavioral Sciences University of California Los Angeles Los Angeles California USA Department of Psychology Northeastern University Boston Massachusetts USA Martinos Center for Biomedical Imaging and Department of Psychiatry Massachusetts General Hospital and Harvard Medical School Boston Massachusetts USA Center for Neural Science New York University New York New York USA Nathan Kline Institute New York State Office of Mental Health New York New York USA Departments of Psychiatry and Child and Adolescent Psychiatry NYU Langone Medical School New York New York USA Division of Depression & Anxiety Disorders McLean Hospital Belmont Massachusetts USA Department of Psychiatry at Harvard Medical School Boston Massachusetts USA Salk Institute for Biological Studies La Jolla California USA
There is disagreement on how best to define and investigate fear. Nature Neuroscience asked Dean Mobbs to lead experts from the fields of human and animal affective neuroscience to discuss their viewpoints on how to d... 详细信息
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