Implementation in Python for Dempster Shafer algorythm with application in predicting movies genres by reviews
"High Frequency" style trading algo based on the Dempster-Shafer fusion theory in C# using the Interactive Brokers API.
Belief functions theory (Dempster-Shafer theory) implementation in C++
A fuzzy machine learning algorithm utilizing Dempster-Shafer and Bayesian Theory
Original PyTorch implementation of AIStats 2025 paper: Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion
A python package of evidence theory
Efficient evidence theory (Dempster-Shafer) calculations for Python
TPS ET RAPPORTS MODULE RCR 1 et 2
📐 Sensor fusion for object classification based on dempster-schafer theory
General-purpose C++ library for Dempster-Shafer Theory (DST)
This library is developed to perform efficient and exact computation of Dempster's and Fagin-Halpern conditionals (DS-Conditional-One and DS-Conditional-All in C++)
A library for working with evidence theory models.
SmartFusion is an IoT-based air quality monitoring system that enhances CO gas detection accuracy using multi-sensor data fusion. It integrates MQ-7 and DHT11 sensors with Kalman Filtering and Dempster–Shafer theory, transmitting real-time data via MQTT and HTTP to a cloud-connected Python gateway.
A Class Inference Scheme With Dempster-Shafer Theory for Learning Fuzzy-Classifier Systems
Intent classification framework based on Dempster-Shafer (DS) theory, designed for uncertainty-aware, hierarchical decision-making
Reproducible multi-source Dempster–Shafer workflow for 1-m urban green-space mapping
Evidence-based belief reasoning models in Python. Implementation based on the multi-layer belief model for academic purposes.
This library provides a linear time and space algorithm for computing all the Fagin-Halpern conditional beliefs generated from consonant belief functions
MIST (Multi-layered Intelligence & Screening Technology) : An AI-powered border security system for identity and document screening using multi-model document forensics, OCR/MRZ analysis, face verification, liveness detection, watchlist screening, and explainable risk assessment.
This reposity present an approach to build 2D evidential occupancy grid maps with Lidar data
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