Multiclass Classification Based on the Convolutional Fuzzy Neural Networks

The paper presents a solution to the multiclass classification problem based on the Convolutional Fuzzy Neural Networks. The proposed model includes a fuzzy self-organization layer for data clustering (in addition to convolutional, pooling and fully-connected layers). The model combines the power of convolutional neural networks and fuzzy logic, it is capable of handling uncertainty and imprecision in the input pattern representation. The Convolutional Fuzzy Neural Networks could provide better accuracy in multiclass classification tasks when classified objects are often characterized by uncertainty and inaccuracy in their representation.