ranging.
Image (source from [3]): Laser triangular ranging principle
At present, many fans [1] [2] have developed laser radar or range finder Based on Laser triangular ranging. This method is also used in this article. In addition to this article, refer to [3] for more details. (The author of this paper is the company that uses low-cost Lidar for home robot XV-11 developers, so I won't talk about it here :-)
The following is an excerpt from the pape
Code download: supervised part-of-speech tagging Based on Hidden Markov Model
Part-of-speech tagging (part-of-speech tagging or POS tagging) means assigning a proper part of
Calculation of the Chinese part of speech tag Set version 3.0: Liu Qun Zhang Huaping Zhang Hao calculation of the Chinese part of the word tag set 10. Description 11. Noun (one class, 7 two class, 5 three classes) 22. Time Word (one class, one two Class) 23. Place of words (one class) 34. Nouns of locality (one class) 35. Verbs (one class, 9 two classes) 36. Adje
(Translator's note: At railsconf July this year held in February 2006, David Heinemeier Hasson gave a keynote speech about the rest design in rails 1.2, and the rest style brings about innovations in Web application design. The first time I saw this video, I thought it could be a historical presentation on Web server development. At that time, I listened to the speech and translated the
Software Overview
Thulac (Thu lexical analyzer for Chinese) is a Chinese lexical analysis toolkit developed by the natural language processing and Social humanities computing laboratory of Tsinghua University. It has the Chinese word segmentation and part-of-speech tagging functions. Thulac has the following features:
Strong capabilities. We are trained using the world's largest human word segmentation an
12, lose -- be lost13, get to know -- know 14, turn on -- be on15, get up -- be up 16, sit down -- sit/be seated17, join -- be in (...) Or be... Member 18, become -- beConnected verb
Used to connect the subject and table language. The verb is often followed by an adjective.① Commonly used links include be, become, go, turn, look, grow, feel, fall, sit, get, seem, etc.② Some connected verbs come from actual verbs, and their meanings also change, for example, grow (grow → become), look (look → lo
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