In the paper, the general structure of some programming objects useful in linguistic analysis is suggested. The structure of the most abstract linguistic object is discussed; such an object can serve as the root of the hierarchy of linguistic objects. We suggest that this abstract linguistic object be a linguistic sign. Two possible methods for hierarchy of linguistic programming objects constr...

Using object clusters for hierarchical radiosity greatly improves the efficiency and thus usability of radiosity computations. By eliminating the quadratic starting phase very large scenes containing about 100k polygons can be handled efficiently. Although the main algorithm extends rather easily to using object clusters, the creation of ’good’ object hierarchies is a difficult task both in ter...

Convolutional Neural Networks (CNN) have been rigorously studied for Hyperspectral Image Classification (HSIC) and are known to be effective in exploiting joint spatial-spectral information with the expense of lower generalization performance learning speed due hard labels non-uniform distribution over labels. Therefore, this paper proposed an idea enhance CNN HSIC using soft that a weighted av...

Raytracing is a method to produce photo-realistic pictures. For each pixel of an image one ray is shot to nd the object, which determines the color of the pixel. Rays are also used to simulate shadows and reeections. Previously bounding volume hierarchies have been used to speed raytracing. A new method to speed the traversal of a bounding volume hierarchy is presented. Optimisation methods to ...

Primate visual systems process natural images in a hierarchical manner: at the early stage, neurons are tuned to local image features, while neurons in high-level areas are tuned to abstract object categories. Standard models of visual processing assume that the transition of tuning from image features to object categories emerges gradually along the visual hierarchy. Direct tests of such model...

We begin with the hypothesis that a model must be able to understand individual objects and relationships between in order generate complex scenes multiple well. Our layout-to-image-generation method, which we call Object-Centric Generative Adversarial Network (or OC-GAN), relies on novel Scene-Graph Similarity Module (SGSM). The SGSM learns representations of spatial scene, lead our model's im...