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• W79875119 abstract "Optical flow computation in dynamic image processing can be formulated as a minimization problem by a variational approach. Because solving the problem is computationally intensive, we reformulate the problem in a way suitable for neural computing. In this paper, we propose a recurrent neural network model that may be implemented in hardware with many processing elements (neurons) operating asynchronously in parallel to achieve a possible real-time solution. We derive and prove the properties of the reformulation, as well as analyze the asymptotic stability and convergence rate of the proposed neural network. Experiments using both the test patterns and the real laboratory images are conducted." @default.
• W79875119 created "2016-06-24" @default.
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• W79875119 date "1998-01-01" @default.
• W79875119 modified "2023-09-26" @default.
• W79875119 title "A Neural Network Model for Optical Flow Computation" @default.
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• W79875119 doi "https://doi.org/10.1016/b978-012526420-4/50003-3" @default.
• W79875119 hasPublicationYear "1998" @default.
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