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Under this assumption, an approach is discussed, based on both neural network and mathematical morphology. It requires neither a starting classification, nor an ...
Abstract. In cluster analysis, the mode boundaries are a very important part of the hierarchy of structures that link raw data with their interpretation.
Aug 1, 2001 · An approach is discussed, based on both neural network and mathematical morphology. It requires neither a starting classification, nor an a priori number of ...
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Sep 16, 2019 · This paper presents a neuronal morphology classification approach based on locally cumulative connected deep neural networks.
Morphological transformations are an efficient method for shape analysis and representation. In this work the pecstrum (pattern spectrum), ...
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This paper proposes an efficient and lightweight Gabor Convolutional Network (GCN) for neuron morphology classification based on the geometric shape data of ...
Sep 4, 2019 · In this paper, a morphological neural network is proposed to address this problem. Serving as a nonlinear feature extracting layer in deep learning frameworks.
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Won, Y., Gader, P.D.: Morphological Shared Weight Neural Network for Pattern Classification and Automatic Target Detection. In: Proc. 1995 IEEE ...
Feb 16, 2021 · This paper presents an interpretable neural system—termed Evolving Long-term Cognitive Network—for pattern classification.
Oct 22, 2024 · Dendrite morphological neurons (DMNs) are neural models for pattern classification, where dendrites are represented by a geometric shape ...