全文获取类型
收费全文 | 32616篇 |
免费 | 4528篇 |
国内免费 | 2348篇 |
专业分类
电工技术 | 891篇 |
综合类 | 2307篇 |
化学工业 | 7373篇 |
金属工艺 | 675篇 |
机械仪表 | 1186篇 |
建筑科学 | 471篇 |
矿业工程 | 1229篇 |
能源动力 | 432篇 |
轻工业 | 10261篇 |
水利工程 | 201篇 |
石油天然气 | 968篇 |
武器工业 | 195篇 |
无线电 | 2377篇 |
一般工业技术 | 1295篇 |
冶金工业 | 1500篇 |
原子能技术 | 508篇 |
自动化技术 | 7623篇 |
出版年
2024年 | 152篇 |
2023年 | 584篇 |
2022年 | 1026篇 |
2021年 | 1294篇 |
2020年 | 1360篇 |
2019年 | 1115篇 |
2018年 | 1049篇 |
2017年 | 1214篇 |
2016年 | 1302篇 |
2015年 | 1498篇 |
2014年 | 2040篇 |
2013年 | 2453篇 |
2012年 | 3370篇 |
2011年 | 2995篇 |
2010年 | 2071篇 |
2009年 | 1930篇 |
2008年 | 1808篇 |
2007年 | 2237篇 |
2006年 | 1931篇 |
2005年 | 1493篇 |
2004年 | 1154篇 |
2003年 | 1011篇 |
2002年 | 762篇 |
2001年 | 599篇 |
2000年 | 544篇 |
1999年 | 432篇 |
1998年 | 347篇 |
1997年 | 317篇 |
1996年 | 241篇 |
1995年 | 207篇 |
1994年 | 145篇 |
1993年 | 132篇 |
1992年 | 140篇 |
1991年 | 92篇 |
1990年 | 87篇 |
1989年 | 64篇 |
1988年 | 42篇 |
1987年 | 43篇 |
1986年 | 35篇 |
1985年 | 34篇 |
1984年 | 36篇 |
1983年 | 24篇 |
1982年 | 16篇 |
1981年 | 15篇 |
1980年 | 13篇 |
1979年 | 7篇 |
1978年 | 6篇 |
1977年 | 6篇 |
1959年 | 6篇 |
1951年 | 6篇 |
排序方式: 共有10000条查询结果,搜索用时 15 毫秒
991.
In this paper, we propose new methods for palmprint classification and handwritten numeral recognition by using the contourlet features. The contourlet transform is a new two dimensional extension of the wavelet transform using multiscale and directional filter banks. It can effectively capture smooth contours that are the dominant features in palmprint images and handwritten numeral images. AdaBoost is used as a classifier in the experiments. Experimental results show that the contourlet features are very stable features for invariant palmprint classification and handwritten numeral recognition, and better classification rates are reported when compared with other existing classification methods. 相似文献
992.
Bimodal biometrics has been found to outperform single biometrics and are usually implemented using the matching score level or decision level fusion, though this fusion will enable less information of bimodal biometric traits to be exploited for personal authentication than fusion at the feature level. This paper proposes matrix-based complex PCA (MCPCA), a feature level fusion method for bimodal biometrics that uses a complex matrix to denote two biometric traits from one subject. The method respectively takes the two images from two biometric traits of a subject as the real part and imaginary part of a complex matrix. MCPCA applies a novel and mathematically tractable algorithm for extracting features directly from complex matrices. We also show that MCPCA has a sound theoretical foundation and the previous matrix-based PCA technique, two-dimensional PCA (2DPCA), is only one special form of the proposed method. On the other hand, the features extracted by the developed method may have a large number of data items (each real number in the obtained features is called one data item). In order to obtain features with a small number of data items, we have devised a two-step feature extraction scheme. Our experiments show that the proposed two-step feature extraction scheme can achieve a higher classification accuracy than the 2DPCA and PCA techniques. 相似文献
993.
Palaiahnakote Shivakumara Author Vitae Weihua Huang Author Vitae Author Vitae Chew Lim Tan Author Vitae 《Pattern recognition》2010,43(6):2165-2185
Detection of both scene text and graphic text in video images is gaining popularity in the area of information retrieval for efficient indexing and understanding the video. In this paper, we explore a new idea of classifying low contrast and high contrast video images in order to detect accurate boundary of the text lines in video images. In this work, high contrast refers to sharpness while low contrast refers to dim intensity values in the video images. The method introduces heuristic rules based on combination of filters and edge analysis for the classification purpose. The heuristic rules are derived based on the fact that the number of Sobel edge components is more than the number of Canny edge components in the case of high contrast video images, and vice versa for low contrast video images. In order to demonstrate the use of this classification on video text detection, we implement a method based on Sobel edges and texture features for detecting text in video images. Experiments are conducted using video images containing both graphic text and scene text with different fonts, sizes, languages, backgrounds. The results show that the proposed method outperforms existing methods in terms of detection rate, false alarm rate, misdetection rate and inaccurate boundary rate. 相似文献
994.
Kerem Altun Author Vitae Author Vitae Orkun Tunçel Author Vitae 《Pattern recognition》2010,43(10):3605-3620
This paper provides a comparative study on the different techniques of classifying human activities that are performed using body-worn miniature inertial and magnetic sensors. The classification techniques implemented and compared in this study are: Bayesian decision making (BDM), a rule-based algorithm (RBA) or decision tree, the least-squares method (LSM), the k-nearest neighbor algorithm (k-NN), dynamic time warping (DTW), support vector machines (SVM), and artificial neural networks (ANN). Human activities are classified using five sensor units worn on the chest, the arms, and the legs. Each sensor unit comprises a tri-axial gyroscope, a tri-axial accelerometer, and a tri-axial magnetometer. A feature set extracted from the raw sensor data using principal component analysis (PCA) is used in the classification process. A performance comparison of the classification techniques is provided in terms of their correct differentiation rates, confusion matrices, and computational cost, as well as their pre-processing, training, and storage requirements. Three different cross-validation techniques are employed to validate the classifiers. The results indicate that in general, BDM results in the highest correct classification rate with relatively small computational cost. 相似文献
995.
In knowledge discovery in a text database, extracting and returning a subset of information highly relevant to a user's query is a critical task. In a broader sense, this is essentially identification of certain personalized patterns that drives such applications as Web search engine construction, customized text summarization and automated question answering. A related problem of text snippet extraction has been previously studied in information retrieval. In these studies, common strategies for extracting and presenting text snippets to meet user needs either process document fragments that have been delimitated a priori or use a sliding window of a fixed size to highlight the results. In this work, we argue that text snippet extraction can be generalized if the user's intention is better utilized. It overcomes the rigidness of existing approaches by dynamically returning more flexible start-end positions of text snippets, which are also semantically more coherent. This is achieved by constructing and using statistical language models which effectively capture the commonalities between a document and the user intention. Experiments indicate that our proposed solutions provide effective personalized information extraction services. 相似文献
996.
A novel set of moment invariants based on the Krawtchouk moments are introduced in this paper. These moment invariants are computed over a finite number of image intensity slices, extracted by applying an innovative image representation scheme, the image slice representation (ISR) method. Based on this technique an image is decomposed to a several non-overlapped intensity slices, which can be considered as binary slices of certain intensity. This image representation gives the advantage to accelerate the computation of image's moments since the image can be described in a number of homogenous rectangular blocks, which permits the simplification of the computation formulas. The moments computed over the extracted slices seem to be more efficient than the corresponding moments of the same order that describe the whole image, in recognizing the pattern under processing. The proposed moment invariants are exhaustively tested in several well known computer vision datasets, regarding their rotation, scaling and translation (RST) invariant recognition performance, by resulting to remarkable outcomes. 相似文献
997.
H.D. Cheng Author Vitae Juan Shan Author Vitae Author Vitae Yanhui Guo Author Vitae Author Vitae 《Pattern recognition》2010,43(1):299-317
Breast cancer is the second leading cause of death for women all over the world. Since the cause of the disease remains unknown, early detection and diagnosis is the key for breast cancer control, and it can increase the success of treatment, save lives and reduce cost. Ultrasound imaging is one of the most frequently used diagnosis tools to detect and classify abnormalities of the breast. In order to eliminate the operator dependency and improve the diagnostic accuracy, computer-aided diagnosis (CAD) system is a valuable and beneficial means for breast cancer detection and classification. Generally, a CAD system consists of four stages: preprocessing, segmentation, feature extraction and selection, and classification. In this paper, the approaches used in these stages are summarized and their advantages and disadvantages are discussed. The performance evaluation of CAD system is investigated as well. 相似文献
998.
999.
1000.
对ETL多数据流并行抽取进行内容与流程的监控,并对各监控模块作了详细分析与设计,监控提高了数据抽取的效率与数据质量,有效保证了系统稳定运行与数据抽取的顺利进行。 相似文献