Image segmentation is an important and fundamental task in computer vision. Its performance is mainly influenced by feature representations and segmentation algorithms. In this paper, we propose a novel clustering-based image segmentation approach which can be called ICDP algorithm. It is able to capture the inherent structure of image and detect the nonspherical clusters. Compared to the other segmentation methods based on clustering, there are several advantages as follows: (1) Integral channel features are used to clearly and comprehensively represent the input image by naturally integrating heterogeneous sources of information; (2) cluster number can be determined directly and cluster centers are able to be identified automatically; (3) hierarchical segmentation is easy to be achieved via ICDP algorithm. The PSNR and MSE are applied to quantitatively evaluate the segmentation performance. Experimental results clearly demonstrate the effectiveness of our novel image segmentation algorithm.
In LDA model, independence assumptions in the Dirichlet distribution of the topic proportions lead to the inability to model the connections between topics. Some researchers have attempted to break them and thus obtained more powerful topic models. Following this strategy, by using an association matrix to measure the association between latent topics, we develop an associated topic model (ATM), in which consecutive sentences are considered important and the topic assignments for words are jointly determined by the association matrix and the sentence level topic distributions, instead of the document-specific topic distributions only. This approach gives a more realistic modeling of latent topic connections where the presence of a topic may be connected with the presence of another. We derive a collapsed Gibbs sampling algorithm for inference and parameter estimation for the ATM. The experimental results demonstrate that the ATM gives a more practical interpretation and is capable of learning more associated topics.
Zirconium diboride (ZrB2) ceramics were prepared by reactive hot pressing of ZrB+B powder mixture. Formation of a transient liquid due to eutectic reaction of ZrB2+Zr→Leu(ZrB2+Zr) at 1661°C following peritectic decomposition of 2ZrB=ZrB2+Zr at 1250°C during heating up of the ZrB+B mixture facilitated densification. The liquid phase was subsequently eliminated via reaction of B with Zr in the eutectic liquid Leu(ZrB2+Zr) to result in a dense ZrB2 ceramic. Full density was reached after reactive hot pressing at 1900°C under 30 MPa for 1 h. The ZrB2 ceramic had a refined microstructure consisting of grains of <1.5 μm in size and relatively good Vickers hardness (21 ± 2 GPa) and flexural strength (595 ± 63 MPa). 相似文献
Dense dual Y3+-Yb3+-doped α-SiAlON ceramic containing extra addition of 2 wt.% Y2O3/Yb2O3 was fabricated by hot pressing at 1900 °C for 1 h, and its optical transmittance was investigated over the wavelength range 200-6000 nm. The results showed that the addition of 2 wt.% extra liquid phase could effectively promote Y/Yb-α-SiAlONs densification and its assemblage only consisted of single crystallized α-SiAlON phase. The obtained sample had relatively high infrared light transmittance properties. The maximum transmittance in the medium infrared region for 1.0 mm thick specimen could reach around 72% at ~ 2500 nm. It is attributed to the uniform, dense microstructure and few residual intergranular phases. 相似文献