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211.
José A. de França Author Vitae Marcelo R. Stemmer Author Vitae 《Pattern recognition》2010,43(3):1180-1187
In recent years, the camera calibration using 1D patterns has been studied and improved by researchers all over the world. However, the progress in that area has been mainly in the sense of reducing the restrictions to the 1D pattern movement. On the other hand, the method's accuracy still demands improvements. In the present paper, the original technique proposed by Zhang is revisited and we demonstrate that the method's accuracy can be significantly improved, simply by analyzing and reformulating the problem. The numerical conditioning can be improved if a simple data normalization is performed. Furthermore, a non-linear solution based on the Partitioned Levenberg-Marquardt algorithm is proposed. That solution takes advantage of the problem's particular structure to reduce the computational complexity of the original method and to improve the accuracy. Tests using both synthetic and real images demonstrate that the calibration method using 1D patterns can be applied in practice, with accuracy comparable to other already traditional methods. 相似文献
212.
In this paper we propose a new circularity measure which defines the degree to which a shape differs from a perfect circle. The new measure is easy to compute and, being area based, is robust—e.g., with respect to noise or narrow intrusions. Also, it satisfies the following desirable properties:
- •
- it ranges over (0,1] and gives the measured circularity equal to 1 if and only if the measured shape is a circle;
- •
- it is invariant with respect to translations, rotations and scaling.
213.
214.
Iris recognition has been widely used in several scenarios with very satisfactory results. As it is one of the earliest stages, the image segmentation is in the basis of the process and plays a crucial role in the success of the recognition task. In this paper we analyze the relationship between the accuracy of the iris segmentation process and the error rates of three typical iris recognition methods. We selected 5000 images of the UBIRIS, CASIA and ICE databases that the used segmentation algorithm can accurately segment and artificially simulated four types of segmentation inaccuracies. The obtained results allowed us to conclude about a strong relationship between translational segmentation inaccuracies – that lead to errors in phase – and the recognition error rates. 相似文献
215.
Luis de-Marcos José Ramón Hilera Roberto Barchino Lourdes Jiménez José Javier Martínez José Antonio Gutiérrez José María Gutiérrez Salvador Otón 《Computers & Education》2010
Mobile learning is considered an evolution of e-learning that embraces the ubiquitous nature of current computational systems in order to improve teaching and learning. Within this context it is possible to develop mobile applications oriented to learning, but it is also important to assess to what extent such applications actually work. In this paper we present a new tool designed to reinforce students’ knowledge by means of self-assessment. Improvement in student achievement was evaluated and an attitudinal survey was also carried out to measure student attitudes towards this new tool. Three different experimental groups were selected for this research, with students aged from 14 to 21 years old, including high-school and university students. Results show that this kind of tool improves student achievement, especially amongst younger learners, with a relatively low impact on current teaching activities and methodology. 相似文献
216.
Soledad Escolar Díaz Florin Isaila Alejandro Calderón Mateos Luis Miguel Sanchez García David E. Singh 《The Journal of supercomputing》2010,51(1):76-93
In the last years the Wireless Sensor Networks’ (WSN) technology has been increasingly employed in various application domains.
The extensive use of WSN posed new challenges in terms of both scalability and reliability. This paper proposes Sensor Node
File System (SENFIS), a novel file system for sensor nodes, which addresses both scalability and reliability concerns. SENFIS
can be mainly used in two broad scenarios. First, it can transparently be employed as a permanent storage for distributed
TinyDB queries, in order to increase the reliability and scalability. Second, it can be directly used by a WSN application
for permanent storage of data on the WSN nodes. The experimental section shows that SENFIS implementation makes an efficient
use of resources in terms of energy consumption, memory footprint, flash wear levelling, while achieving execution times similarly
with existing WSN file systems. 相似文献
217.
An adaptive, real-time, traffic monitoring system 总被引:1,自引:0,他引:1
In this paper we describe a computer vision-based traffic monitoring system able to detect individual vehicles in real-time.
Our fully integrated system first obtains the main traffic variables: counting, speed and category; and then computes a complete
set of statistical variables. The objective is to investigate some of the difficulties impeding existing traffic systems to
achieve balanced accuracy in every condition; i.e. day and night transitions, shadows, heavy vehicles, occlusions, slow traffic
and congestions. The system we present is autonomous, works for long periods of time without human intervention and adapts
automatically to the changing environmental conditions. Several innovations, designed to deal with the above circumstances,
are proposed in the paper: an integrated calibration and image rectification step, differentiated methods for day and night,
an adaptive segmentation algorithm, a multistage shadow detection method and special considerations for heavy vehicle identification
and treatment of slow traffic. A specific methodology has been developed to benchmark the accuracy of the different methods
proposed. 相似文献
218.
Pablo Quintía Roberto Iglesias Miguel A. Rodríguez Carlos V. Regueiro 《Robotics and Autonomous Systems》2010,58(12):1306-1315
One of the main problems of robots is the lack of adaptability and the need for adjustment every time the robot changes its working place. To solve this, we propose a learning approach for mobile robots using a reinforcement-based strategy and a dynamic sensor-state mapping. This strategy, practically parameterless, minimises the adjustments needed when the robot operates in a different environment or performs a different task.Our system will simultaneously learn the state space and the action to execute on each state. The learning algorithm will attempt to maximise the time before a robot failure in order to obtain a control policy suited to the desired behaviour, thus providing a more interpretable learning process. The state representation will be created dynamically, starting with an empty state space and adding new states as the robot finds new situations that has not seen before. A dynamic creation of the state representation will avoid the classic, error-prone and cyclic process of designing and testing an ad hoc representation. We performed an exhaustive study of our approach, comparing it with other classic strategies. Unexpectedly, learning both perception and action does not increase the learning time. 相似文献
219.
David Schleicher Luis M. Bergasa Manuel Ocaña Rafael Barea Elena López 《Robotics and Autonomous Systems》2010,58(8):991-1002
In this paper we present a new real-time hierarchical (topological/metric) Visual SLAM system focusing on the localization of a vehicle in large-scale outdoor urban environments. It is exclusively based on the visual information provided by a cheap wide-angle stereo camera. Our approach divides the whole map into local sub-maps identified by the so-called fingerprints (vehicle poses). At the sub-map level (low level SLAM), 3D sequential mapping of natural landmarks and the robot location/orientation are obtained using a top-down Bayesian method to model the dynamic behavior. A higher topological level (high level SLAM) based on fingerprints has been added to reduce the global accumulated drift, keeping real-time constraints. Using this hierarchical strategy, we keep the local consistency of the metric sub-maps, by mean of the EKF, and global consistency by using the topological map and the MultiLevel Relaxation (MLR) algorithm. Some experimental results for different large-scale outdoor environments are presented, showing an almost constant processing time. 相似文献
220.
N. Ruiz Reyes P. Vera Candeas S. García Galán J.E. Muñoz 《Engineering Applications of Artificial Intelligence》2010,23(2):151-159
Automatic discrimination of speech and music is an important tool in many multimedia applications. The paper presents a robust and effective approach for speech/music discrimination, which relies on a two-stage cascaded classification scheme. The cascaded classification scheme is composed of a statistical pattern recognition classifier followed by a genetic fuzzy system. For the first stage of the classification scheme, other widely used classifiers, such as neural networks and support vector machines, have also been considered in order to assess the robustness of the proposed classification scheme. Comparison with well-proven signal features is also performed. In this work, the most commonly used genetic learning algorithms (Michigan and Pittsburgh) have been evaluated in the proposed two-stage classification scheme. The genetic fuzzy system gives rise to an improvement of about 4% in the classification accuracy rate. Experimental results show the good performance of the proposed approach with a classification accuracy rate of about 97% for the best trial. 相似文献