semantic image 中文意思是什麼
semantic image
解釋
語義心象-
A fuzzy image data model and a concept of fuzzy space are proposed, in which model visual feature, spatial feature and semantic feature are used for super feature in order to utilize advantage of traditional relation database as well as characteristics of image data and fuzzy retrieval. based fuzzy space, a method of similarity measurement of image is presented to support fuzzy features - based image retrieval and satisfy user ' s query requirement for image. in the thesis, a semantic template and the mechanism of dynamic relevant feedback are defined so that it can express user ' s query semantic and improve retrieval precision and useable capability for image retrieval
研究了模糊檢索方法和相關反饋機制在圖象檢索中的應用，提出了一種模糊圖象數據模型和模糊空間的概念，該模型將可視特徵、空間特徵、語義特徵看作超屬性，既充分利用了傳統關系數據庫的優點，同時又考慮了圖象數據以及模糊查詢的特點，文中提出的模糊空間和模糊相似性度量方法能支持基於模糊特徵的圖象查詢，較好地體現用戶圖象查詢的應用需求，文中定義的語義模板和相關反饋機制能在一定程度上表達用戶的查詢語義，提高圖象檢索的準確率和易用性。 -
Image semantic classification by using svm
基於支持向量機的圖像語義分類 -
Experimental results show that the proposed approach is more accurate in image semantic classification than other ones, such as svms classifier using color and textural features
實驗結果表明，本文提出的方法在圖像語義分類的準確性方面要優于諸如採用色彩特徵和紋理特徵的支持向量機分類器的其它方法。 -
This paper takes the right of publicity of real person as the research object, using the comparative analytic method and semantic analytic method, combining the domestic and international newest cases, drawing lessons from the domestic and international scholar ’ s existing research results, to prove the necessity and meaning of setting up the independent right of publicity of real person. this paper attempts to found a new kind of right, namely the right of publicity of real person, to promote the abundant legal protection of the real person ’ s image interests
本文以真實人物形象權作為研究對象，運用實證分析方法下的比較分析法和語義分析法，結合國內外最新的案例，借鑒國內外學者已有的研究成果，論證了建立獨立的真實人物形象權的必要性和意義，試圖通過創設一種新型的權利，即真實人物形象權，實現對真實人物形象利益的充分法律保護。 -
“ semantic gap ” is the gulf between the low - level image visual feature and high - level concepts, the images can be different of semantic concept while having similar visual feature, and they can also be different of visual feature while having the same concept
「語義鴻溝」是指圖像的低級視覺特徵和高級語義特徵之間的差距，由計算機計算出來的低級特徵的相關性很難說明圖像在語義層上的相似性，語義層上的相似性也無法證明低級特徵的相關性。 -
The query strategy for historic building image database based on semantic network
基於語義網路的古建築圖像數據庫的查詢策略 -
The experimental system extract the low - level features of images such as hsv histogram, the texture got from coexistence matrix, color correlogram, and according to the characteristic of our image database, design the evaluation function such as the average rank ratio to evaluate and compare the performance of different integration of different features including semantic, and validate the active effect of feedback using experiment results
該原型系統提取了hsv直方圖、共生矩陣紋理、顏色相關圖等底層特徵，同時根據圖像數據庫的特點，設計了平均位置比值等評價函數對語義特徵與底層特徵的各種結合的檢索性能進行了比較分析，並對反饋效果進行了實驗驗證。 -
Secondly, because the avility of expressing image semantic informations with the color feature is too limited, so a texture feature is presented, we discuss the mothed of extracting texture of image
其次，考慮到單純顏色特徵對圖像語義信息表示能力的不足，引入了對圖像的紋理屬性進行分析，討論紋理特徵提取的各種演算法，確定提取圖像的紋理特徵矢量演算法。 -
This paper discusses the characters of semantic objects in lung ct images, the methods of extracting semantic objects from lung ct images, the methods of classification the semantic objects with svm and the creating and using of semantic objects tables in lung ct image database
摘要主要討論了支持基於語義查詢的肺部ct圖像庫中語義對象的特點，基於支持向量機分類的語義對象提取方法，及相應的語義對象庫表的建立和使用。 -
A new image sampling method and a device for transmission flow measuring are provided, and an edge detection method based on the semantic weight and threshold selection tactics based on the vision model are used to extract the contour, calculate the area and volume within a short time span
設計了一種新型的用於傳輸流量檢測的圖像採集方法和裝置，並利用基於語義權值的邊緣提取方法和基於視覺模型的閾值選擇策略進行傳輸帶上物質的截面輪廓線提取，計算物質截面面積和較短時間內的流量體積。 -
The framework suppose that the image ' s semantic feature can be expressed by using a multi - level attribute tree, and the probability of a certain image having a certain attribute can be estimated by interpolation method using the neighboring image ' s value. here, the neighboring relation refers to the neighboring in the low - level feature space
該框架假定圖像的語義特徵可用多層屬性樹來近似表示，並且圖像擁有某個屬性的概率值可由相鄰的圖像的概率值進行插值估計，框架中的相鄰指圖像在底層特徵空間的相鄰。 -
Firstly, one image retrieval framework based on “ fuzzy semantic relevant matrix ” ( fsrm ) is proposed, which uses users ’ relevance feedback sufficiently
首先提出了一種基於「模糊語義相關矩陣」的圖像檢索模型，該模型充分利用了用戶的反饋。 -
Firstly, the original image data is reduced to segmentation, which can be implemented, by low - pass filters and media filters, etc ; secondly, features of image data, i. e. color component, texture, motion, frame difference and semantic information will be extracted ; thirdly, the determination to segmentation with some uniform standard is made based on the features
本方案是基於像素點的聚類，分割得到的對象具有較好的邊緣效果並且不需要預先設定門限值。由於神經網路具有超強的容錯性，使得本方案對于受噪聲污染的圖像也具有一定的適應性。 -
However, this technology still faces much difficulty to bridge the semantic gap between image semantic features and the lower features, resulting in the fact that the extracted content features still mainly centered upon the lower features such as color, texture and shape
然而，由於圖像語義特徵和低層特徵的「鴻溝」問題，給圖像檢索技術帶來了很大困難，目前提取的內容特徵仍集中於顏色、紋理、形狀等低層特徵。 -
The paper shows as well that the image structure and canonical epistemic states can be used not only to get the representation result for wci - recovering contraction relation, but also to provide semantic characterizations for a wide range of recovering contraction relations
我們在文中還指出圖像結構以及典範認知狀態不但能刻畫wci -可恢復收縮關系的表示定理，而且能就多種可恢復收縮關系給出他們的語義表示。 -
In recent year, content - based image retrieval ( cbir ) has been an increasingly active research, cbir is very useful in various areas, but is extremely difficult to put into use, because the computer has very limited ability in understanding and analyzing the semantic content of the image
=基於內容的視頻信號和圖像數據庫檢索的研究，是近年來非常活躍的研究領域。它有著極其廣闊的應用前景，但解決起來卻又極為困難，難度主要在於計算機對于圖像的理解，很難對圖像的內容進行語義上的解釋。 -
As we know, retrieving image through semantic features is the most desirable and useful way. in this thesis, a semantic feature databases built dynamically based on relevance feedback was proposed
提出基於種子圖像為檢索範例圖像，採用相關性反饋的方法來動態構造語義特徵數據庫，最終實現基於語義的圖像檢索方法。 -
Relevance feedback techniques are important approaches closing up the semantic gap between high - level concepts and low - level features in image retrieval effectively, and efficient indexing schemes for high - dimensional data are required for real - time retrieval in large - scale image database
相關反饋方法是彌合圖像檢索中高層語義和低層特徵之間語義間隔的一個重要途徑，而有效的高維索引機制則是面向大規模圖像庫的檢索能夠達到實時性要求的關鍵技術。
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