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21.
Nikolaos Gianniotis Christoph Schnörr Christian Molkenthin Sanjay Singh Bora 《Pattern Analysis & Applications》2016,19(2):475-485
Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower bound on the desired integral to be approximated, e.g. marginal likelihood. The lower bound is then optimised with respect to its free parameters, the so-called variational parameters. However, this is not always possible as for certain integrals it is very challenging (or tedious) to come up with a suitable lower bound. Here, we propose a simple scheme that overcomes some of the awkward cases where the usual variational treatment becomes difficult. The scheme relies on a rewriting of the lower bound on the model log-likelihood. We demonstrate the proposed scheme on a number of synthetic and real examples, as well as on a real geophysical model for which the standard variational approaches are inapplicable. 相似文献
22.
The design of a high pressure (HP) cell for neutron reflectivity experiments is described. The cell can be used to study solid-liquid interfaces under pressures up to 2500 bar (250 MPa). The sample interface is based on a thick silicon block with an area of about 14 cm(2). This area is in contact with the sample solution which has a volume of only 6 cm(3). The sample solution is separated from the pressure transmitting medium, water, by a thin flexible polymer membrane. In addition, the HP cell can be temperature-controlled by a water bath in the range 5-75°C. By using an aluminum alloy as window material, the assembled HP cell provides a neutron transmission as high as 41%. The maximum angle of incidence that can be used in reflectivity experiments is 7.5°. The large accessible pressure range and the low required volume of the sample solution make this HP cell highly suitable for studying pressure-induced structural changes of interfacial proteins, supported lipid membranes, and, in general, biomolecular systems that are available in small quantities, only. To illustrate the performance of the HP cell, we present neutron reflectivity data of a protein adsorbate under high pressure and a lipid film which undergoes several phase transitions upon pressurization. 相似文献
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We study the price of anarchy and the structure of equilibria in network creation games. A network creation game is played by n players {1,2,…,n}, each identified with a vertex of a graph (network), where the strategy of player i, i=1,…,n, is to build some edges adjacent to i. The cost of building an edge is α>0, a fixed parameter of the game. The goal of every player is to minimize its creation cost plus its usage cost. The creation cost of player i is α times the number of built edges. In the SumGame variant, the usage cost of player i is the sum of distances from i to every node of the resulting graph. In the MaxGame variant, the usage cost is the eccentricity of i in the resulting graph of the game. In this paper we improve previously known bounds on the price of anarchy of the game (of both variants) for various ranges of α, and give new insights into the structure of equilibria for various values of α. The two main results of the paper show that for α>273?n all equilibria in SumGame are trees and thus the price of anarchy is constant, and that for α>129 all equilibria in MaxGame are trees and the price of anarchy is constant. For SumGame this answers (almost completely) one of the fundamental open problems in the field—is price of anarchy of the network creation game constant for all values of α?—in an affirmative way, up to a tiny range of α. 相似文献
25.
Christoph Spengler Marcus Huber Andreas Gabriel Beatrix C. Hiesmayr 《Quantum Information Processing》2013,12(1):269-278
Entanglement in high-dimensional many-body systems plays an increasingly vital role in the foundations and applications of quantum physics. In the present paper, we introduce a theoretical concept which allows to categorize multipartite states by the number of degrees of freedom being entangled. In this regard, we derive computable and experimentally friendly criteria for arbitrary multipartite qudit systems that enable to examine in how many degrees of freedom a mixed state is genuine multipartite entangled. 相似文献
26.
Félix Gómez Mármol Christoph Sorge Ronald Petrlic Osman Ugus Dirk Westhoff Gregorio Martínez Pérez 《International Journal of Information Security》2013,12(2):67-82
The recent deployment of smart grids promises to bring numerous advantages in terms of energy consumption reduction in both homes and businesses. A more transparent and instantaneous measurement of electricity consumption through smart meters utilization leads to an enhancement in the ability of monitoring, controlling and predicting energy usage. Nevertheless, it also has associated drawbacks related to the privacy of customers, since such management might reveal their personal habits, which electrical appliances they are using at each moment, whether they are at home or not, etc. In this work, we present a privacy-enhanced architecture for smart metering aimed at tackling this threat by means of encrypting individual measurements while allowing the electricity supplier to access the aggregation of the corresponding decrypted values. 相似文献
27.
This letter presents an improved cue integration approach to reliably separate coherent moving objects from their background scene in video sequences. The proposed method uses a probabilistic framework to unify bottom-up and top-down cues in a parallel, "democratic" fashion. The algorithm makes use of a modified Bayes rule where each pixel's posterior probabilities of figure or ground layer assignment are derived from likelihood models of three bottom-up cues and a prior model provided by a top-down cue. Each cue is treated as independent evidence for figure-ground separation. They compete with and complement each other dynamically by adjusting relative weights from frame to frame according to cue quality measured against the overall integration. At the same time, the likelihood or prior models of individual cues adapt toward the integrated result. These mechanisms enable the system to organize under the influence of visual scene structure without manual intervention. A novel contribution here is the incorporation of a top-down cue. It improves the system's robustness and accuracy and helps handle difficult and ambiguous situations, such as abrupt lighting changes or occlusion among multiple objects. Results on various video sequences are demonstrated and discussed. (Video demos are available at http://organic.usc.edu:8376/ approximately tangx/neco/index.html .). 相似文献
28.
We describe a neural network able to rapidly establish correspondence between neural feature layers. Each of the network's two layers consists of interconnected cortical columns, and each column consists of inhibitorily coupled subpopulations of excitatory neurons. The dynamics of the system builds on a dynamic model of a single column, which is consistent with recent experimental findings. The network realizes dynamic links between its layers with the help of specialized columns that evaluate similarities between the activity distributions of local feature cell populations, are subject to a topology constraint, and can gate the transfer of feature information between the neural layers. The system can robustly be applied to natural images, and correspondences are found in time intervals estimated to be smaller than 100 ms in physiological terms. 相似文献
29.
M. Cristani A. Perina U. Castellani V. Murino 《Pattern Recognition and Image Analysis》2009,19(2):245-252
Image categorization is undoubtedly one of the most recent and challenging problems faced in Computer Vision. The scientific
literature is plenty of methods more or less efficient and dedicated to a specific class of images; further, commercial systems
are also going to be advertised in the market. Nowadays, additional data can also be attached to the images, enriching its
semantic interpretation beyond the pure appearance. This is the case of geo-location data that contain information about the
geographical place where an image has been acquired. This data allow, if not require, a different management of the images,
for instance, to the purpose of easy retrieval from a repository, or of identifying the geographical place of an unknown picture,
given a geo-referenced image repository. This paper constitutes a first step in this sense, presenting a method for geo-referenced
image categorization, and for the recognition of the geographical location of an image without such information available.
The solutions presented are based on robust pattern recognition techniques, such as the probabilistic Latent Semantic Analysis,
the Mean Shift clustering and the Support Vector Machines. Experiments have been carried out on a couple of geographical image
databases: results are actually very promising, opening new interesting challenges and applications in this research field.
The article is published in the original.
Marco Cristani received the Laurea degree in 2002 and the Ph.D. degree in 2006, both in Computer Science from the University of Verona,
Verona, Italy.
He was a visiting Ph.D. student at the Computer Vision Lab, Institute for Robotics and Intelligent Systems School of Engineering
(IRIS), University of Southern California, Los Angeles, in 2004–2005. He is now an Assistant Professor with the Department
of Computer Science, University of Verona, working with the Vision, Image Processing and Sounds (VIPS) Lab. His main research
interests include statistical pattern recognition, generative modeling via graphical models, and non-parametric data fusion
techniques, with applications on surveillance, segmentation and image and video retrieval.
He is the author of several papers in the above subjects and a reviewer for several international conferences and journals.
Alessandro Perina received the BD and MS degrees in Information Technologies and Intelligent and Multimedia Systems from the University of
Verona, Verona, Italy, in 2004 and 2006, respectively. He is currently a Ph.D. candidate in the Computer Science Department
at the University of Verona. His research interests include computer vision, machine learning and pattern recognition. He
is a student member of the IEEE.
Umberto Castellani is Ricercatore (i.e., Research Assistant) of Department of Computer Science at University of Verona. He received his Dottorato
di Ricerca (Ph.D.) in Computer Science from the University of Verona in 2003 working on 3D data modelling and reconstruction.
During his Ph.D., he had been Visiting Research Fellow at the Machine Vision Unit of the Edinburgh University, in 2001. In
2007 he has been an Invited Professor for two months at the LASMEA laboratory in Clermont-Ferrand, France. In 2008, he has
been Visiting Researcher for two months at the PRIP laboratory of the Michigan State University (USA). His main research interests
concern the processing of 3D data coming from different acquisition systems such as 3D models from 3D scanners, acoustic images
for the vision in underwater environment, and MRI scans for biomedical applications. The addressed methodologies are focused
on the intersections among Machine Learning, Computer Vision and Computer Graphics.
Vittorio Murino received the Laurea degree in electronic engineering in 1989 and the Ph.D. degree in electronic engineering and computer
science in 1993, both from the University of Genoa, Genoa, Italy.
He is a Full Professor with the Department of Computer Science, University of Verona. From 1993 to 1995, he was a Postdoctoral
Fellow in the Signal Processing and Understanding Group, Department of Biophysical and electronic Engineering, University
of Genoa, where he supervised of research activities on image processing for object recognition and pattern classification
in underwater environments. From 1995 to 1998, he was an Assistant Professor of the Department of Mathematics and Computer
Science, University of Udine, Udine, Italy. Since 1998, he has been with the University of Verona, where he founded and is
responsible for the Vision, Image processing, and Sound (VIPS) Laboratory. He is scientifically responsible for several national
and European projects and is an Evaluator for the European Commission of research project proposals related to different scientific
programmes and frameworks. His main research interests include computer vision and pattern recognition, probabilistic techniques
for image and video processing, and methods for integrating graphics and vision. He is author or co-author of more than 150
papers published in refereed journals and international conferences.
Dr. Murino is a referee for several international journals, a member of the technical committees for several conferences (ECCV,
ICPR, ICIP), and a member of the editorial board of Pattern Recognition, IEEE Transactions on Systems, Man, and Cybernetics,
Pattern Analysis and Applications and Electronic Letters on Computer Vision and Image Analysis (ELCVIA). He was the promotor
and Guest Editor off our special issues of Pattern Recognition and is a Fellow of the IAPR. 相似文献
30.