Semantic gap
Bridging the Semantic Gap in Content Based Image Retrieval
... Because these individual features are generally agreed to be low level in nature, investigators have proposed unique feature detection algorithms in an effort to bridge the semantic gap. Combinations of ...
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An Approach to Explore the Role of Color Models and Color Descriptors in the Optimization of Semantic Gap in Content based Image Retrieval
... In this work, the performance of a wide variety of color models in combination with different color descriptors for semantically meaningful content based image retrieval is presented and evaluated. The main question ...
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An efficient algorithm eradicating semantic gap with help of image quality assessment
... This architecture works as same to the previous model. In this the function is passed to nonlinear function. This function gives the value as to the function. This is passed to degradation where the quality of image is ...
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Virtual machine introspection: towards bridging the semantic gap
... We expect the following outcomes from our manuscript. We believe that it will provide a guide for future developers of VMI tools looking to develop various applications for cloud security and malware detec- tion based on ...
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Semantic gap in CBIR: automatic objects spatial relationships semantic extraction and representation
... towards semantic based image retrieval and the main problem encountered in the content- based image retrieval research is the semantic gap between the low-level feature representing and high-level ...
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The Reality of the Semantic Gap in Image Retrieval
... the gap vary from one problem to ...the semantic gap starts at the descriptors and goes all the way up to the ...a gap may remain between the labels and the ...
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Bridging the Semantic Gap in Multimedia Information Retrieval: Top down and Bottom up approaches
... the semantic gap in multimedia retrieval have mostly used an auto-annotation approach, in which keyword annotations are applied to unlabelled ...the semantic gap using Latent Semantic ...
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Significance of Context Sensitiveness in Content based Image Retrieval System and Bridging the Semantic Gap
... Efficient categorization of images can be performed, if the mapping between semantics and image features is well defined by the system. By this process, the semantic gap can be reduced. The representation ...
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An Efficient Algorithm to Reduce the Semantic Gap between Image Contents and Tags
... However, semantic gap is a major problem in the image processing ...of semantic gap by applying techniques to extract low level features of an image such as color, texture and ...
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Mind the Semantic Gap
... internally. Semantic Web technologies often require very detailed authoring, the creation of ontolo- gies, and complex authoring tools if authors are to produce semantic data ...
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Bridging the Semantic Gap
... latent semantic indexing (LSI) and image statistics are computed using color histogram and texture orientation ...supports semantic matching of ...Latent semantic analysis has been used by Pham et ...
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Using Intermediate Representations to Solve Math Word Problems
... This paper presents an intermediate meaning rep- resentation scheme for math problem solving that bridges the semantic gap between natural lan- guage and equation systems. To generate inter- mediate forms, ...
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Image Retrieval Using Textual Pre filtering and Visual Re ranking
... We discussed a detailed description of textual pre-filtering techniques. These textual pre-filtering techniques reduce in a suitable way the size of the multimedia database thus improving the final fused image retrieval ...
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A REVIEW: FROM KEYWORD BASED IMAGE RETRIEVAL TO ONTOLOGY BASED IMAGE RETRIEVAL
... “semantic gap” [11]. It is a gap between the high level image grasping of a human mind and the low level image estimation from ...‘semantic gap’ has the following varieties: describing ...
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A Content Based Image Retrieval Using Soft Computing Technique Vikram Verma, Rachna Rajput
... ‘semantic gap’ include mainly five categories: (1) using object ontology to define high-level concepts, (2) using machine learning tools to associate low level features with query concepts, (3) introducing ...
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A Survey on Automatic Summarization Using Multi-Modal Summarization System for Asynchronous Collections
... transcriptions. For visual information, including the key frames extracted from videos and the images that appear in documents learn the joint representations of text and images with a neural network; then identify the ...
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RevUP: Automatic Gap Fill Question Generation from Educational Texts
... generating gap-fill questions. RevUP consists of 3 parts: Sentence Se- lection, Gap Selection & Multiple Choice Distractor ...select gap-phrases from each selected sentence, we collected human ...
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Mind the Gap : Quantifying the pension savings gap in Europe
... The pension savings gap we have identified presents a huge challenge. Everyone, at every stage of their working lives, must be aware of the need to make appropriate provision for their retirement. It is a critical ...
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Lateralized semantic priming: modulation by levodopa, semantic distance, and participants’ magical beliefs
... hyperactive RH language system caused “loosening” of associations. Of specific interest to the role of DA as different for the two hemispheres of the brain is the finding that acutely psychotic patients and healthy ...
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Semantic Kernels for Semantic Parsing
... it with the string “::L”, where L is the first let- ter of the POS-tags of the words, e.g., along, my and route, receive i, p and n, which are the first letters of the POS-tags IN, PRN and NN, respec- tively. SK applied ...
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