• FCM construction (manual construction based on Experts, and automatic construction based on input data). Visualization of the constructed FCM with nodes and weighted arcs.
• FCM learning (Evolutionary and Hebbian algorithms)
• FCM inference (Kosko, Stylios and Rescaled).

A tool that combines state-of-the-art Convolutional Neural Networks for feature extraction and feature selection, algorithms for feature clustering, and Fuzzy Cognitive Maps for feature classification.

A library that includes the application of Convolutional Neural Networks for feature extraction of images and Fuzzy Cognitive Maps learning for classification of instances.

A library that utilizes state-of-the-art Convolutional Neural Networks, and Post-Hoc explainability methods such as Grad-CAM and DeepSHAP for image classification.

A python library that utilizes autoencoder neural network architectures for anomaly detection.