Edge Prior Multilayer Segmentation Network Based on Bayesian Framework
نویسندگان
چکیده
منابع مشابه
On Bayesian Network Approximation by Edge Deletion
We consider the problem of deleting edges from a Bayesian network for the purpose of simplifying models in probabilistic inference. In particular, we propose a new method for deleting network edges, which is based on the evidence at hand. We provide some interesting bounds on the KL-divergence between original and approximate networks, which highlight the impact of given evidence on the quality...
متن کاملHand gesture recognition based on dynamic Bayesian network framework
In this paper, we propose a new method for recognizing hand gestures in a continuous video stream using a dynamic Bayesian network or DBN model. The proposed method of DBN-based inference is preceded by steps of skin extraction and modelling, and motion tracking. Then we develop a gesture model for oneor two-hand gestures. They are used to define a cyclic gesture network for modeling continuous...
متن کاملBayesian reconstruction based on flexible prior models
A new approach to Bayesian reconstruction is proposed that endows the prior probability distribution with an inherent geometrical flexibility, which is achieved through a transformation of the coordinate system of the prior distribution or model into that of the reconstruction. With this warping, prior morphological information regarding the object that is being reconstructed may be adapted to ...
متن کاملMAP–Based Framework for Segmentation of MR Brain Images Based on Visual Appearance and Prior Shape
We propose a new MAP-based technique for the unsupervised segmentation of different brain structures (white matter, gray matter, etc.) from T1-weighted MR brain images. In this paper, we follow a procedure like most conventional approaches, in which T1-weighted MR brain images and desired maps of regions (white matter, gray matter, etc.) are modeled by a joint Markov-Gibbs Random Field model (M...
متن کاملIntelligent Edge Detection using a CUDA Simulator of Multilayer Neural Network Based on Multi-Valued Neurons
In this paper, we consider the edge detection problem using an intelligent approach. We use a multilayer neural network based on multi-valued neurons (MLMVN) as an intelligent edge enhancer. MLMVN is a complex-valued neural network and it has many advantages over classical neural networks. It significantly outperforms a classical multilayer feedforward neural network in terms of learning speed,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Sensors
سال: 2020
ISSN: 1687-725X,1687-7268
DOI: 10.1155/2020/6854260