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991.
Multiset canonical correlation analysis (MCCA) is a powerful technique for analyzing linear correlations among multiple representation data. However, it usually fails to discover the intrinsic geometrical and discriminating structure of multiple data spaces in real-world applications. In this paper, we thus propose a novel algorithm, called graph regularized multiset canonical correlations (GrMCCs), which explicitly considers both discriminative and intrinsic geometrical structure in multiple representation data. GrMCC not only maximizes between-set cumulative correlations, but also minimizes local intraclass scatter and simultaneously maximizes local interclass separability by using the nearest neighbor graphs on within-set data. Thus, it can leverage the power of both MCCA and discriminative graph Laplacian regularization. Extensive experimental results on the AR, CMU PIE, Yale-B, AT&T, and ETH-80 datasets show that GrMCC has more discriminating power and can provide encouraging recognition results in contrast with the state-of-the-art algorithms. 相似文献
992.
This paper addresses a multi-supplier, multi-affected area, multi-relief, and multi-vehicle relief allocation problem in disaster relief logistics. A multi-objective optimisation model based on disaster scenario information updates is proposed in an attempt to coordinate efficiency and equity through timely and appropriate decisions regarding issues such as vehicle routing and relief allocation. An optimal stopping rule is also proposed to determine the optimum period of delay before responding to disaster, because decision making requires accurate disaster information. The main contribution of this paper is solving relief allocation problem in a novel way by correlating operational research with statistical decision making and Bayesian sequential analysis. Finally, a case is presented based on the post-disaster rescue in Eastern China after supertyphoon Saomai to test the applicability and show the potential advantages of the proposed model. 相似文献
993.
《Pattern recognition》2014,47(2):721-735
Mathematical morphology offers popular image processing tools, successfully used for binary and grayscale images. Recently, its extension to color images has become of interest and several approaches were proposed. Due to various issues arising from the vectorial nature of the data, none of them imposed as a generally valid solution. We propose a probabilistic pseudo-morphological approach, by estimating two pseudo-extrema based on Chebyshev inequality. The framework embeds a parameter which allows controlling the linear versus non-linear behavior of the probabilistic pseudo-morphological operators. We compare our approach for grayscale images with the classical morphology and we emphasize the impact of this parameter on the results. Then, we extend the approach to color images, using principal component analysis. As validation criteria, we use the estimation of the color fractal dimension, color textured image segmentation and color texture classification. Furthermore, we compare our proposed method against two widely used approaches, one morphological and one pseudo-morphological. 相似文献
994.
《Pattern recognition》2014,47(2):556-567
For face recognition, image features are first extracted and then matched to those features in a gallery set. The amount of information and the effectiveness of the features used will determine the recognition performance. In this paper, we propose a novel face recognition approach using information about face images at higher and lower resolutions so as to enhance the information content of the features that are extracted and combined at different resolutions. As the features from different resolutions should closely correlate with each other, we employ the cascaded generalized canonical correlation analysis (GCCA) to fuse the information to form a single feature vector for face recognition. To improve the performance and efficiency, we also employ “Gabor-feature hallucination”, which predicts the high-resolution (HR) Gabor features from the Gabor features of a face image directly by local linear regression. We also extend the algorithm to low-resolution (LR) face recognition, in which the medium-resolution (MR) and HR Gabor features of a LR input image are estimated directly. The LR Gabor features and the predicted MR and HR Gabor features are then fused using GCCA for LR face recognition. Our algorithm can avoid having to perform the interpolation/super-resolution of face images and having to extract HR Gabor features. Experimental results show that the proposed methods have a superior recognition rate and are more efficient than traditional methods. 相似文献
995.
There is evidence that biological and physiological systems including the brain exhibit can exhibit fractal characteristics that can be used to identify the state of the system. In this study, wavelet-based fractal analysis is used to examine self-similar or scale-invariant characteristics of intracranial EEG data in terms of the spectral exponent. The intracranial EEG data were recorded from subjects with epilepsy during non-seizure period and during epileptic seizure activity. From the computational results, it is observed that the self-similar or scale-invariant characteristics of the intracranial EEG data obtained during these two periods are significantly different. The actual value of the estimated spectral exponent depends on the wavelet bases used for the computations. 相似文献
996.
8‐hydroxy‐5‐azoquinolinephenylacrylate‐formaldehyde (8H5AQPA‐F) macromonomer was prepared from acryloylchloride, with condensation products of 8‐hydroxy‐5‐azoquinolinephenol‐formaldehyde, and polymerized in DMF at 70°C using benzoyl peroxide as free radical initiator. Poly(8H5AQPA‐F) was characterized by infrared and nuclear magnetic resonance spectroscopic techniques. Polychelates were obtained in alkaline solution of polymeric ligand, with the aqueous solution of Cu(II) and Ni(II). Elemental analysis of polychelates suggests that the metal to ligand ratio is about 1:2. The polymer metal complexes were also characterized by IR, XRD, magnetic moments, and thermal analysis. The effects of pH and electrolyte on the metal uptake behavior of the resin were also studied. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 797–802, 2007 相似文献
997.
The main biochemical function of the tocopherols is believed to be the protection of polyunsaturated fatty acids (PUFA) against
peroxidation. A critical question that must be asked in reference to this is whether there is a biochemical link between the
tocopherol levels and the degree of unsaturation in vegetable oils, the main source of dietary PUFA and vitamin E. We used
a mathematical approach in an effort to highlight some facts that might help address this question. Literature data on the
relative composition of fatty acids (16:0, 16:1, 18:0, 18:1, 18:2, and 18:3) and the contents of tocopherols (α-, β-, δ-,
and γ-tocopherol) in 101 oil samples, including 14 different botanical species, were analyzed by principal-component analysis
and linear regression. There was a negative correlation between α- and γ-tocopherols (r=0.633, P<0.05). Results also showed a positive correlation between linoleic acid (18:2) and α-tocopherol (r=0.549, P<0.05) and suggested a positive correlation between linolenic acid (18:3) and γ-tocopherol. 相似文献
998.
999.
Product development of today is becoming increasingly knowledge intensive. Specifically, design teams face considerable challenges in making effective use of increasing amounts of information. In order to support product information retrieval and reuse, one approach is to use case-based reasoning (CBR) in which problems are solved “by using or adapting solutions to old problems.” In CBR, a case includes both a representation of the problem and a solution to that problem. Case-based reasoning uses similarity measures to identify cases which are more relevant to the problem to be solved. However, most non-numeric similarity measures are based on syntactic grounds, which often fail to produce good matches when confronted with the meaning associated to the words they compare. To overcome this limitation, ontologies can be used to produce similarity measures that are based on semantics. This paper presents an ontology-based approach that can determine the similarity between two classes using feature-based similarity measures that replace features with attributes. The proposed approach is evaluated against other existing similarities. Finally, the effectiveness of the proposed approach is illustrated with a case study on product–service–system design problems. 相似文献
1000.