本文關(guān)鍵詞：人工智能、模式識(shí)別在氣象領(lǐng)域應(yīng)用的現(xiàn)狀與展望，由筆耕文化傳播整理發(fā)布。

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計(jì)算機(jī)軟件及計(jì)算機(jī)應(yīng)用

模式識(shí)別與人工智能

     The VLPR system involves the techniques of digital image processing, computer vision, pattern recognition and artificial intelligence and so on.

     VLPR系統(tǒng)的研究涉及數(shù)字圖像處理、計(jì)算機(jī)視覺、模式識(shí)別與人工智能等多個(gè)技術(shù)領(lǐng)域，其關(guān)鍵技術(shù)包括車牌定位、字符分割、字符識(shí)別等。

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     The VLPR system involves the techniques of digital image processing, computer vision, pattern recognition and artificial intelligence and so on.

     VLPR系統(tǒng)的研究涉及數(shù)字圖象處理、計(jì)算機(jī)視覺、模式識(shí)別與人工智能等多個(gè)技術(shù)領(lǐng)域，其關(guān)鍵技術(shù)包括車牌定位、字符分割、字符識(shí)別等。

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     This paper presents the image analysis and recognition in spinal diseases by using the digital image processing techniques,theories and methods associated with pattern recognition and artificial intelligence.

     本文將數(shù)字圖象處理技術(shù)、模式識(shí)別與人工智能的理論和方法用于脊柱疾病的圖象分析與識(shí)別.

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     Computer visual technique,which is an important field of the pattern recognition and artificial intelligence, has been used in many aspects of food industry.

     計(jì)算機(jī)視覺技術(shù)是模式識(shí)別與人工智能的一個(gè)重要領(lǐng)域,其應(yīng)用已擴(kuò)展到食品行業(yè)的諸多方面。

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     Computer visual technique, which is an important field of the pattern recognition and artificial intelligence, has been used in many aspects of agriculture.

     計(jì)算機(jī)視覺技術(shù)是模式識(shí)別與人工智能的一個(gè)重要領(lǐng)域,其應(yīng)用已擴(kuò)展到農(nóng)業(yè)領(lǐng)域的諸多方面。

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     Speaker recognition is a branch of speech signal processing, it involves a lot of fields, such as the acoustics, phonetics, linguistics, physiology, psychology, information engineering, communication theory, electronic technique, computer science, pattern recognition, artificial intelligence etc, and is a interdisciplinary application field.

     說話人識(shí)別是一類特殊的語音識(shí)別，，它并不在意語音信號(hào)中的語義內(nèi)容，而只強(qiáng)調(diào)各個(gè)說話人之間的特征差異，希望從語音信號(hào)中提取說話人的個(gè)性特征。 說話人識(shí)別是語音信號(hào)處理的一個(gè)分支，涉及到語音學(xué)、語音信號(hào)處理、模式識(shí)別與人工智能等學(xué)科，是跨學(xué)科的綜合性應(yīng)用研究領(lǐng)域。

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     This paper is written on the background of the project of N-1 Style Intelligent Road Surface Disease Inspection Vehicle of Department of Computer Science of Nanjing University of Science and Technology. It aims to improve the system architecture and to study the automatic inspection algorithm of diseases in road surface images.

     本文的工程背景是南京理工大學(xué)計(jì)算機(jī)系模式識(shí)別與人工智能實(shí)驗(yàn)室的N—1型道路狀況智能檢測車項(xiàng)目，目的是對(duì)系統(tǒng)的體系結(jié)構(gòu)進(jìn)行改進(jìn)，對(duì)路面病害自動(dòng)檢測算法進(jìn)行研究。

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     Because EHW has ability of self-adapting to environment and quickly self-recombinedits structure, we can predict that evolution technology of hardware will be applied extensivelyto design of electro circuit, automatic control, system of compatible error, mode identify andartificial intelligence, intelligent robot, outer space, deep ocean and so on. Especially, itopened up broad prospects for Aviation and Deep Ocean.

     可以預(yù)言:硬件進(jìn)化技術(shù)將被廣泛應(yīng)用于電路設(shè)計(jì)、自動(dòng)控制、容錯(cuò)系統(tǒng)、模式識(shí)別與人工智能、智能機(jī)器人、太空和深海等領(lǐng)域,尤其在航空、航天領(lǐng)域?qū)⒄宫F(xiàn)廣闊的應(yīng)用前景。

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     In recent years, scientific workers have used fire protection, civil security, fire science, image processing technology, infrared detection, computer vision, pattern-recognition with artificial intelligent, computer network, and so on. All kinds of new and high technology have developed the products of fire detection, improving the monitor capability to the fire.

     近年來,科學(xué)工作者綜合運(yùn)用了消防、民用安全、火災(zāi)科學(xué)、圖像技術(shù)、紅外檢測、計(jì)算機(jī)視覺、模式識(shí)別與人工智能及計(jì)算機(jī)網(wǎng)絡(luò)等各高新技術(shù),開發(fā)出相應(yīng)的產(chǎn)品,提高了對(duì)火災(zāi)的防治能力。

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     The problem of automatically tracking the sync-phase axis on the seismic cross-section images via pattern recognition and AI approaches is one of the major topics in seismic data explanation.

     應(yīng)用模式識(shí)別與人工智能技術(shù)解決剖面圖同相軸的自動(dòng)追蹤問題,是目前地震勘探資料自動(dòng)解釋中所研究的主要問題之一.

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     Research of neural networks and pattern recognition

     神經(jīng)網(wǎng)絡(luò)研究與模式識(shí)別

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     Mode S and Military IFF

     S模式與軍用敵我識(shí)別

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     Study of Memory Mode and Artificial Intelligence

     記憶模式與人工智能的研究

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     Application of Artificial Intelligence and Pattern Recognition in Meteorology: Development and Prospect

     人工智能、模式識(shí)別在氣象領(lǐng)域應(yīng)用的現(xiàn)狀與展望

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     Optical Pattern Recognition and Intelligence Processors

     光學(xué)模式識(shí)別和人工智能處理器

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  pattern recognition and artificial intelligence

For the past fifteen years the "Pattern Recognition and Artificial Intelligence" research group at thecrin has been involved in various projects on isolated-word and continuous speech recognition.

Her research area covers computer vision, image processing, pattern recognition and artificial intelligence.

International Journal of Pattern Recognition and Artificial Intelligence, 8, 147-165.

This paper presents the image analysis and recognition in spinal diseases by using the digital image processing techniques,theories and methods associated with pattern recognition and artificial intelligence.Based on this idea,the computer diagnosis system constructed increases the diagnostic reliability of spinal tumor and gives satisfactory results.

本文將數(shù)字圖象處理技術(shù)、模式識(shí)別與人工智能的理論和方法用于脊柱疾病的圖象分析與識(shí)別.由此構(gòu)成的計(jì)算機(jī)診斷系統(tǒng)提高了對(duì)脊柱腫瘤診斷的可信度,經(jīng)臨床試驗(yàn),取得滿意效果.

The problem of automatically tracking the sync-phase axis on the seismic cross-section images via pattern recognition and AI approaches is one of the major topics in seismic data explanation. This paper presents a methol which employs AR model to represent the sync-phase axis and track the axis automatically by a special data structure and searching technique. Compared with the results described in [1] and [2], this method is capable of repairing the broken points, thus keeping the continuity of the axis. It...

The problem of automatically tracking the sync-phase axis on the seismic cross-section images via pattern recognition and AI approaches is one of the major topics in seismic data explanation. This paper presents a methol which employs AR model to represent the sync-phase axis and track the axis automatically by a special data structure and searching technique. Compared with the results described in [1] and [2], this method is capable of repairing the broken points, thus keeping the continuity of the axis. It can also provide useful information about the ends of the axis as well as the broken strata and their locations. The structure of the proposed system can be provided with an interface for knowledge input, thus making it possible to track intelligently.

應(yīng)用模式識(shí)別與人工智能技術(shù)解決剖面圖同相軸的自動(dòng)追蹤問題,是目前地震勘探資料自動(dòng)解釋中所研究的主要問題之一.本文提出了一種區(qū)別于文獻(xiàn)[1,2]的新的AR自動(dòng)追蹤方法,首次應(yīng)用AR模型描述同相軸,在一種特定的數(shù)據(jù)結(jié)構(gòu)和搜索策略下實(shí)現(xiàn)了同相軸的AR自動(dòng)追蹤.與已有的研究結(jié)果相比,該方法能修補(bǔ)斷點(diǎn),保持同相軸的連續(xù)性;對(duì)尖滅和斷層給出了有參考價(jià)值的結(jié)果;并顯示以同相軸劃分的大致層位.該方法在結(jié)構(gòu)上還有引入知識(shí)的接口,從而提供了實(shí)現(xiàn)智能追蹤的可能性.

Abstract

醚菊脂類似物構(gòu)效關(guān)系的人工神經(jīng)網(wǎng)絡(luò)方法的研究蔡煜東，程兆年，汪列，姚林聲，陳念貽（中國科學(xué)院上海冶金研究所上海２０００５０）１人工神經(jīng)網(wǎng)絡(luò)－Ｂ－Ｐ模型及算法Ｂ－Ｐ模型（“反向傳播”模型）的結(jié)構(gòu)與算法見文獻(xiàn)（尹紅風(fēng)等。模式識(shí)別與人工智能，１９９０，３（...

  本文關(guān)鍵詞：人工智能、模式識(shí)別在氣象領(lǐng)域應(yīng)用的現(xiàn)狀與展望，由筆耕文化傳播整理發(fā)布。