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An Oscillatory Neural Network for Image Segmentation

机译:用于图像分割的振荡神经网络

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Oscillatory neural networks are a recent approach for applications in image segmentation. Two positive aspects of such networks are its massively parallel topology and the capacity to separate the segments in time. On the other hand, limitations that restrict the practical application are found in the proposed oscillatory networks, such as the use of differential equations, implying high complexity for implementation in digital hardware, and limited capacity of segmentation. In the present paper, an oscillatory neural network suitable for image segmentation in digital vision chips is presented. This network offers several advantages, including unlimited capacity of segmentation. Preliminary results confirm the successful operation of the proposal in image segmentation and its good potential for real time video segmentation.
机译:振荡神经网络是图像分割中应用的最近方法。这种网络的两个积极方面是其大规模平行的拓扑和能力及时分离段的能力。另一方面,限制了实际应用的限制在所提出的振荡网中找到,例如使用微分方程,这意味着在数字硬件中实现的高复杂性,并且分割容量有限。在本文中,提出了一种适用于数字视觉芯片图像分割的振荡神经网络。该网络提供了几个优点,包括无限的分割容量。初步结果证实了图像分割提案的成功运行及其实时视频分割的良好潜力。

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