Generative models and Bayesian model comparison for shape recognition. Abstract: Recognition of hand-drawn shapes is an important and widely studied problem.
Recognition of hand-drawn shapes is an important and widely studied problem. By adopting a generative proba- bilistic framework we are able to formulate a ...
Recognition of hand-drawn shapes is an important and widely studied problem. By adopting a generative proba- bilistic framework we are able to formulate a ...
This work adopts a generative probabilistic framework and forms a robust and flexible approach to shape recognition which allows for a wide range of shapes ...
Download Citation | Generative models and Bayesian model comparison for shape recognition | Recognition of hand-drawn shapes is an important and widely ...
Dive into the research topics of 'Generative models and Bayesian model comparison for shape recognition'. Together they form a unique fingerprint. Shape Earth ...
Dive into the research topics of 'Generative models and Bayesian model comparison for shape recognition'. Together they form a unique fingerprint. Sort by ...
People also ask
Are generative models Bayesian?
What is model comparison for Bayesian models?
We present an algorithm for shape matching and recognition based on a generative model for how one shape can be generated by the other.
We demonstrate that the proposed model generates realistic samples, generalizes to unseen examples, and is able to handle missing regions and/or background ...
Mar 11, 2024 · We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down ( ...