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  2. Semantic similarity - Wikipedia

    en.wikipedia.org/wiki/Semantic_similarity

    Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content [citation needed] as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of ...

  3. List of CBIR engines - Wikipedia

    en.wikipedia.org/wiki/List_of_CBIR_engines

    An adaptive image browsing system that provides users with an intuitive, easy-to-use, structured view of an image collection and complements it with ideas from the field of adaptable content-based similarity search. A hierarchical view of images (the Browsing Tree) that can be customized according to user preferences is provided. Yes No ...

  4. Similarity search - Wikipedia

    en.wikipedia.org/wiki/Similarity_search

    Similarity search is the most general term used for a range of mechanisms which share the principle of searching (typically very large) spaces of objects where the only available comparator is the similarity between any pair of objects. This is becoming increasingly important in an age of large information repositories where the objects ...

  5. Content-based image retrieval - Wikipedia

    en.wikipedia.org/wiki/Content-based_image_retrieval

    General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey [1] for a scientific overview of the CBIR field).

  6. Structural similarity index measure - Wikipedia

    en.wikipedia.org/wiki/Structural_similarity...

    In order to evaluate the image quality, this formula is usually applied only on luma, although it may also be applied on color (e.g., RGB) values or chromatic (e.g. YCbCr) values. The resultant SSIM index is a decimal value between -1 and 1, where 1 indicates perfect similarity, 0 indicates no similarity, and -1 indicates perfect anti-correlation.

  7. Similarity learning - Wikipedia

    en.wikipedia.org/wiki/Similarity_learning

    It is often applied in nearest neighbor search on large-scale high-dimensional data, e.g., image databases, document collections, time-series databases, and genome databases. [3] A common approach for learning similarity is to model the similarity function as a bilinear form.

  8. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    Images, text Facial expression analysis 2000 [95] [96] T. Kanade et al. JAFFE Facial Expression Database 213 images of 7 facial expressions (6 basic facial expressions + 1 neutral) posed by 10 Japanese female models. Images are cropped to the facial region. Includes semantic ratings data on emotion labels. 213 Images, text Facial expression ...

  9. Latent semantic analysis - Wikipedia

    en.wikipedia.org/wiki/Latent_semantic_analysis

    The use of Latent Semantic Analysis has been prevalent in the study of human memory, especially in areas of free recall and memory search. There is a positive correlation between the semantic similarity of two words (as measured by LSA) and the probability that the words would be recalled one after another in free recall tasks using study lists ...