With the rapid development of cities, semantic segmentation urban scenes, as an important and effective imaging method, can accurately obtain distribution information typical ground features, reflecting scale level greenery in cities. There are some challenging problems point clouds including different scales, imbalanced class distribution, missing data caused by occlusion. Based on cloud netwo...

Police and government agencies make use of facial recognition technology in order to determine the truth about criminal. Though this might seem skeptical, it requires support public come into action. In regard media plays a major role molding agenda attracting sentiments attitudes towards topic. work, various perspectives are taken consideration impact social on public, police with help face te...

Multimodal semantic models attempt to ground distributional semantics through the integration of visual or perceptual information. Feature norms provide useful insight into human concept acquisition, but cannot be used to ground largescale semantics because they are expensive to produce. We present an automatic method for predicting feature norms for new concepts by learning a mapping from a te...

To recognize visual objects, our sensory perceptions are transformed through dynamic neural interactions into meaningful representations of the world but exactly how visual inputs invoke object meaning remains unclear. To address this issue, we apply a regression approach to magnetoencephalography data, modeling perceptual and conceptual variables. Key conceptual measures were derived from sema...

We discuss a method for identifying semantic arguments of a verb from a sentence. It differs from existing methods by an unique feature that represents all semantic arguments of a verb in a syntactic parse tree. The feature is a path in which at least one of the children of a node is a root of a subtree that associates with a semantic argument. Experiments on WSJ data from Penn TreeBank and Pro...