Abstract. Unsupervised learning requires a grouping step that defines which data belong together. A natural way of grouping in images is the segmentation of objects or parts of objects. While pure bottom-up segmentation from static cues is well know
利用高斯混合模型实现图像分割The Expectation-Maximization algorithmhas been classically used to find the maximum likelihood estimates of parameters in probabilistic models with unobserved data, for instance, mixture models. A key issue in such problems is the choi
This paper presents a new machine-learning Chinese word segmentation (CWS) approach, which defines CWS as a break-point classifi- cation problem; the break point is the bound- ary of two subsequent words. Further, this paper exploits a support vecto
Segmenting dynamic contrast enhanced-MRI series of small animal, which are intrinsically noisy and low contrasted images with low resolution, is the aim of this paper. To do this, a segmentation method taking into account the temporal (spectral) and
The random walker algorithm was introduced in the paper: Leo Grady and Gareth Funka-Lea, "Multi-Label Image Segmentation for Medical Applications Based on Graph-Theoretic Electrical Potentials" 随机游走的图像分割技术
