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Convolutional Neural Networks and its contemporary variants have proven to be ruling benchmarks for most image processing tasks but resort to pooling techniques and routing mechanisms that affect classification accuracy and lose spatial relationship information between involved data points.
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Gagan a et al. (2019) studied this question.
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