نتایج جستجو برای: vhr semantic labeling
تعداد نتایج: 162844 فیلتر نتایج به سال:
Semantic role labeling (SRL) is a fundamental task in natural language processing to find a sentence-level semantic representation. At present, the mainstream studies of semantic role labeling focus on the use of a variety of statistical machine learning techniques. But it difficult to obtain high quality labeled data. To solve the problem, we proposed a novel prototype patterns selection algor...
In this paper, we propose a framework to extendsemantic labeling of images to video shot sequences and achieveefficient and semantic-aware spatiotemporal video segmentation.This task faces two major challenges, namely the temporal vari-ations within a video sequence which affect image segmentationand labeling, and the computational cost of region labeling.Guided by these...
We describe a well-performed semantic role labeling system that further extracts concepts (smaller semantic expressions) from unstructured natural language sentences language independently. A dual-layer semantic role labeling (SRL) system is built using Chinese Treebank and Propbank data. Contextual information is incorporated while labeling the predicate arguments to achieve better performance...
Semantic segmentation necessitates approaches that learn high-level characteristics while dealing with enormous quantities of data. Convolutional neural networks (CNNs) can unique and adaptive features to achieve this aim. However, due the large size high spatial resolution remote sensing images, these cannot efficiently analyze an entire scene. Recently, deep transformers have proven their cap...
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