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Learning Covariate Relations in Disease Progression Models Using Symbolic Neural Networks. [PDF]
CPT Pharmacometrics Syst PharmacolSundell J +4 more
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White blood cell classification using custom deep neural network and visualizing features of the images using heatmaps. [PDF]
Sci RepKaraddi SH +3 more
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Proceedings of ICNN'95 - International Conference on Neural Networks, 2002
In this paper, we discuss an approach for designing the computational neural network, which is mainly composed of a hardlimiter neuron, a updated neuron, and a search function neuron, to solve some computational problems. The computation-by-search scheme can effectively solve some complicated problems in the condition that their search functions can be
null Jar-Ferr Yang, null Chi-Ming Chen
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In this paper, we discuss an approach for designing the computational neural network, which is mainly composed of a hardlimiter neuron, a updated neuron, and a search function neuron, to solve some computational problems. The computation-by-search scheme can effectively solve some complicated problems in the condition that their search functions can be
null Jar-Ferr Yang, null Chi-Ming Chen
openaire +1 more source
Optical computing powers graph neural networks
Applied Optics, 2022Graph-based neural networks have promising perspectives but are limited by electronic bottlenecks. Our work explores the advantages of optical neural networks in the graph domain. We propose an optical graph neural network (OGNN) based on inverse-designed optical processing units (OPUs) to classify graphs with optics.
Kaida Tang +5 more
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Computation within cultured neural networks
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2005In this paper we present three related areas of research we are pursuing to study neural computation in vitro. Rat cortical neurons cultured on 60 channel multielectrode array (MEA) allow the researcher to measure from and stimulate sixty different sites across a small population of neurons grown in vitro.
T, DeMarse +4 more
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Computing with neural networks
IEEE Potentials, 1993The resurgence of interest in neural networks is discussed. This interest is prompted by two facts. First, the nervous systems of simple animals can easily solve problems that are very difficult for conventional computers. Second, the ability to model biological nervous system functions using man-made machines increases understanding of that biological
M.N.O. Sadiku, M. Mazzara
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1992
Research on neural network modeling has a long history. Neurobiologists have discovered individual nerve cells existing in the brain and learned how neurons carry information, transmit information, and respond to various stimuli. Based on the understanding of the nervous system, many neural networks have been proposed by researchers.
Yi-Tong Zhou, Rama Chellappa
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Research on neural network modeling has a long history. Neurobiologists have discovered individual nerve cells existing in the brain and learned how neurons carry information, transmit information, and respond to various stimuli. Based on the understanding of the nervous system, many neural networks have been proposed by researchers.
Yi-Tong Zhou, Rama Chellappa
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Layered Neural Networks Computations
Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Networks (SNPD/SAWN'05), 2005Among prominent features of the visual networks, movement detections are carried out in the visual cortex. The visual cortex for the movement detection, consist of two layered networks, called the primary visual cortex (VI), followed by the middle temporal area (MT), in which nonlinear functions play important roles in the visual systems. In this paper,
N. Ishii, T. Deguchi, H. Sasaki
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2007
Brain function remains one of the most elusive and fascinating phenomena challenging modem science (Churchland, 1986). Although a lot is already known about the neuron and its functional characteristics, when we address the information-processing capabilities of a neural assembly, called here the mesoscopic description (Freeman, 1975), more often than ...
Dongming Xu +7 more
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Brain function remains one of the most elusive and fascinating phenomena challenging modem science (Churchland, 1986). Although a lot is already known about the neuron and its functional characteristics, when we address the information-processing capabilities of a neural assembly, called here the mesoscopic description (Freeman, 1975), more often than ...
Dongming Xu +7 more
openaire +1 more source