Recently, convolutional neural network (CNN) has led to significant improvement in the field of computer vision, especially accuracy and speed semantic segmentation tasks, which greatly improved robot scene perception. In this article, we propose a multilevel feature fusion dilated convolution (Refine-DeepLab). By improving space pyramid pooling structure, multiscale hybrid module, captures ric...

Sketch-based modeling has attracted considerable attention in recent years. In this paper, we propose a semantic feature modeling system for sketch-based jewelry design, called Sketch2Jewelry. The newly devised semantic feature class encodes specific domain knowledge (jewelry design knowledge in this paper) and supplies prolific semantic information. The advantage of using semantic features is ...

Purpose: This study investigated two classifications of semantic features, feature importance and relevance, to verify if they differentially influenced lexical knowledge in individuals with aphasia.Methods: A sorting task was utilized 20 volunteer participants aphasia investigate the processing involved association features their appropriate nouns. corpus 18 nouns displayed front each particip...

Objectives: Anomia is one of the most common and persistent symptoms of aphasia. Although treatments of anomia usually focus on semantic and/or phonological levels, which both have been demonstrated to be effective, the relationship between the underlying functional deficit in naming and response to a particular treatment approach remains unclear. The aim of this study was to determine the rela...

multi-word lexical units are a typical feature of specialized dictionaries, in particular monolingual and bilingual maritime dictionaries. the paper studies the concept of the multi-word lexical unit and considers the similarities and differences of their selection and presentation in monolingual and bilingual maritime dictionaries. the work analyses such issues as the classification of multi-w...

Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We...