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GitHub topics: markov-random-fields

stecrotti/BeliefPropagation.jl

The Belief Propagation approximation for probability distributions on sparse graphs

Language: Julia - Size: 1.28 MB - Last synced at: about 3 hours ago - Pushed at: about 4 hours ago - Stars: 25 - Forks: 0

realjules/cvae-quadratreeMRF

A novel semi-supervised framework combining contrastive learning with hierarchical probabilistic graphical models for remote sensing with limited labeled data. Our approach enhances CRFNet by learning discriminative representations from unlabeled imagery while capturing multi-resolution spatial dependencies.

Language: Python - Size: 30.1 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 0 - Forks: 0

aeolusguan/NMRF

[CVPR 2024] Neural Markov Random Field for Stereo Matching

Language: Python - Size: 26.8 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 130 - Forks: 8

anjalichennupati/Video_Anomaly_Detection_Using_MRF

A video anomaly detection system using Markov Random Fields (MRFs) and autoencoders. It extracts frames, segments them using MRFs, and leverages autoencoders for anomaly detection. The system improves detection accuracy and reduces computation time by 60%, making it efficient for real-time surveillance applications.

Language: Jupyter Notebook - Size: 445 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

avani17101/Computer-Vision

Done as part of Computer Vision course assignments(spring 2021) at IIIT Hyderabad.

Language: Jupyter Notebook - Size: 275 MB - Last synced at: over 2 years ago - Pushed at: about 4 years ago - Stars: 7 - Forks: 1

salimandre/Markov-Random-Fields

Image denoising using Markov random fields.

Language: Python - Size: 1.66 MB - Last synced at: over 2 years ago - Pushed at: over 5 years ago - Stars: 4 - Forks: 1

FirstHandScientist/renn

RENN

Language: Python - Size: 810 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 1

netw0rkf10w/NoRELAX-cpp

C++ implementation of the NoRELAX methods presented in Continuous Relaxation of MAP Inference: A Nonconvex Perspective (CVPR 2018)

Language: C++ - Size: 2.39 MB - Last synced at: 8 months ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 0