A novel loss function based on category distribution for semantic segmentation is proposed in this paper. The new composed of two parts: (1) Pixel-wise cross-entropy. (2) Category proposed. Most existing networks adopt a single pixel-wise cross-entropy function, which guides the network to independently predict class each pixel belongs to. downside that ignoring global information image -- all ...

Semantic scene completion (SSC) requires the estimation of 3D geometric occupancies objects in scene, along with object categories. Currently, many methods employ RGB-D images to capture and semantic information objects. These use simple but popular spatial- channel-wise operations, which fuse RGB depth data. Yet, they ignore large discrepancy data uncertainty measurements To solve this problem...

A Semantic Link Network (SLN) consists of nodes (entities, features, concepts, schemas or communities) and semantic links between nodes. This paper proposes an autonomous Semantic Link Network formalism to support intelligent applications on large-scale network. The formalism integrates the SLN logical reasoning with the SLN analogical reasoning and the SLN inductive reasoning as well as existi...