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A Japanese visual dictionary (1887). A visual dictionary is a dictionary that primarily uses pictures to illustrate the meaning of words. [1] Visual dictionaries are often organized by themes, instead of being an alphabetical list of words. For each theme, an image is labeled with the correct word to identify each component of the item in question.
A Visual Encyclopedia, of the Periodic Table Elements; A Visual Encyclopedia, Presidents; A Visual Encyclopedia, People & Places; A Visual Encyclopedia, Sharks & Other Deadly Ocean Creatures; A Visual Encyclopedia, Bible Characters; A Visual History, The Arts; A Visual History, Guns; A Visual History, of Arms & Amour Weapon; A Visual History ...
A Japanese visual dictionary (1887). A conceptual dictionary (also ideographic or ideological dictionary) is a dictionary that groups words by concept or semantic relation instead of arranging them in alphabetical order. Examples of conceptual dictionaries are picture dictionaries, thesauri, and visual dictionaries.
A picture dictionary or pictorial dictionary is a dictionary where the definition of a word is displayed in the form of a drawing or photograph. Picture dictionaries are useful in a variety of teaching environments, such as teaching a young child about their native language, or instructing older students in a foreign language, such as in the Culturally Authentic Pictorial Lexicon.
Microsoft Encarta is a discontinued digital multimedia encyclopedia and search engine published by Microsoft from 1993 to 2009. Originally sold on CD-ROM or DVD, it was also available online via annual subscription, although later articles could also be viewed for free online with advertisements. [1]
Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!
StarDict, developed by Hu Zheng (胡正), is a free GUI released under the GPL-3.0-or-later license for accessing StarDict dictionary files (a dictionary shell). It is the successor of StarDic, developed by Ma Su'an (馬蘇安), continuing its version numbers.
In computer vision, the bag-of-words model (BoW model) sometimes called bag-of-visual-words model [1] [2] can be applied to image classification or retrieval, by treating image features as words. In document classification , a bag of words is a sparse vector of occurrence counts of words; that is, a sparse histogram over the vocabulary.
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