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1.
Rough sets   总被引:1295,自引:0,他引:1295  
We investigate in this paper approximate operations on sets, approximate equality of sets, and approximate inclusion of sets. The presented approach may be considered as an alternative to fuzzy sets theory and tolerance theory. Some applications are outlined.  相似文献
2.
A Tutorial on Support Vector Machines for Pattern Recognition   总被引:661,自引:0,他引:661  
The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in detail. We describe a mechanical analogy, and discuss when SVM solutions are unique and when they are global. We describe how support vector training can be practically implemented, and discuss in detail the kernel mapping technique which is used to construct SVM solutions which are nonlinear in the data. We show how Support Vector machines can have very large (even infinite) VC dimension by computing the VC dimension for homogeneous polynomial and Gaussian radial basis function kernels. While very high VC dimension would normally bode ill for generalization performance, and while at present there exists no theory which shows that good generalization performance is guaranteed for SVMs, there are several arguments which support the observed high accuracy of SVMs, which we review. Results of some experiments which were inspired by these arguments are also presented. We give numerous examples and proofs of most of the key theorems. There is new material, and I hope that the reader will find that even old material is cast in a fresh light.  相似文献
3.
Support-Vector Networks   总被引:541,自引:0,他引:541  
Thesupport-vector network is a new learning machine for two-group classification problems. The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space. In this feature space a linear decision surface is constructed. Special properties of the decision surface ensures high generalization ability of the learning machine. The idea behind the support-vector network was previously implemented for the restricted case where the training data can be separated without errors. We here extend this result to non-separable training data.High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated. We also compare the performance of the support-vector network to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.  相似文献
4.
Least Squares Support Vector Machine Classifiers   总被引:322,自引:0,他引:322  
In this letter we discuss a least squares version for support vector machine (SVM) classifiers. Due to equality type constraints in the formulation, the solution follows from solving a set of linear equations, instead of quadratic programming for classical SVM's. The approach is illustrated on a two-spiral benchmark classification problem.  相似文献
5.
Induction of decision trees   总被引:322,自引:2,他引:320  
The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directions.  相似文献
6.
基于条件信息熵的决策表约简   总被引:302,自引:8,他引:294  
Rough集理论是近年来发展起来的一种有效地处理不精确、不确定、含糊信息的数学理论方法,在机器学习、数据挖掘、智能数据分析、控制算法获取等领域取得了很大的成功。研究者从不同的角度对这个理论进行研究。本文将从信息论观点出发对Rough集理论的基本概念和主要运算进行分析讨论,通过与Rough集理论的代数观点进行比较分析,得到这两种观点下的一些等价性质和不同的特性,并基于条件信息熵提出决策表的约简算法。  相似文献
7.
Color indexing   总被引:281,自引:0,他引:281  
Computer vision is embracing a new research focus in which the aim is to develop visual skills for robots that allow them to interact with a dynamic, realistic environment. To achieve this aim, new kinds of vision algorithms need to be developed which run in real time and subserve the robot's goals. Two fundamental goals are determining the location of a known object. Color can be successfully used for both tasks.This article demonstrates that color histograms of multicolored objects provide a robust, efficient cue for indexing into a large database of models. It shows that color histograms are stable object representations in the presence of occlusion and over change in view, and that they can differentiate among a large number of objects. For solving the identification problem, it introduces a technique calledHistogram Intersection, which matches model and image histograms and a fast incremental version of Histogram Intersection, which allows real-time indexing into a large database of stored models. For solving the location problem it introduces an algorithm calledHistogram Backprojection, which performs this task efficiently in crowded scenes.  相似文献
8.
Snakes: Active contour models   总被引:262,自引:6,他引:256  
A snake is an energy-minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines and edges. Snakes are active contour models: they lock onto nearby edges, localizing them accurately. Scale-space continuation can be used to enlarge the capture region surrounding a feature. Snakes provide a unified account of a number of visual problems, including detection of edges, lines, and subjective contours; motion tracking; and stereo matching. We have used snakes successfully for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest.  相似文献
9.
Bagging Predictors   总被引:242,自引:0,他引:242  
Bagging predictors is a method for generating multiple versions of a predictor and using these to get an aggregated predictor. The aggregation averages over the versions when predicting a numerical outcome and does a plurality vote when predicting a class. The multiple versions are formed by making bootstrap replicates of the learning set and using these as new learning sets. Tests on real and simulated data sets using classification and regression trees and subset selection in linear regression show that bagging can give substantial gains in accuracy. The vital element is the instability of the prediction method. If perturbing the learning set can cause significant changes in the predictor constructed, then bagging can improve accuracy.  相似文献
10.
基于Arnold变换的数字图像置乱技术   总被引:228,自引:6,他引:222  
针对近年来兴起的数字图像信息安全问题,从Arnold变换出发,给出了在位置空间和色彩空间上对数字图像进行置乱的方法,这些方法简便易行,可以用来作为数字图像隐藏和伪装的预处理。  相似文献
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