全文获取类型
收费全文 | 39501篇 |
免费 | 7121篇 |
国内免费 | 3754篇 |
专业分类
电工技术 | 10835篇 |
技术理论 | 4篇 |
综合类 | 3700篇 |
化学工业 | 1328篇 |
金属工艺 | 585篇 |
机械仪表 | 3648篇 |
建筑科学 | 1681篇 |
矿业工程 | 2507篇 |
能源动力 | 1046篇 |
轻工业 | 704篇 |
水利工程 | 920篇 |
石油天然气 | 2689篇 |
武器工业 | 538篇 |
无线电 | 3297篇 |
一般工业技术 | 2098篇 |
冶金工业 | 895篇 |
原子能技术 | 187篇 |
自动化技术 | 13714篇 |
出版年
2024年 | 157篇 |
2023年 | 867篇 |
2022年 | 1589篇 |
2021年 | 1936篇 |
2020年 | 2004篇 |
2019年 | 1432篇 |
2018年 | 1291篇 |
2017年 | 1461篇 |
2016年 | 1536篇 |
2015年 | 1856篇 |
2014年 | 2875篇 |
2013年 | 2376篇 |
2012年 | 3278篇 |
2011年 | 3346篇 |
2010年 | 2490篇 |
2009年 | 2602篇 |
2008年 | 2508篇 |
2007年 | 2975篇 |
2006年 | 2506篇 |
2005年 | 2045篇 |
2004年 | 1753篇 |
2003年 | 1521篇 |
2002年 | 1209篇 |
2001年 | 1018篇 |
2000年 | 830篇 |
1999年 | 691篇 |
1998年 | 450篇 |
1997年 | 323篇 |
1996年 | 311篇 |
1995年 | 278篇 |
1994年 | 185篇 |
1993年 | 133篇 |
1992年 | 107篇 |
1991年 | 85篇 |
1990年 | 72篇 |
1989年 | 43篇 |
1988年 | 32篇 |
1987年 | 22篇 |
1986年 | 21篇 |
1985年 | 19篇 |
1984年 | 19篇 |
1983年 | 22篇 |
1982年 | 11篇 |
1981年 | 16篇 |
1980年 | 16篇 |
1979年 | 10篇 |
1978年 | 9篇 |
1977年 | 7篇 |
1975年 | 6篇 |
1951年 | 4篇 |
排序方式: 共有10000条查询结果,搜索用时 356 毫秒
1.
引入句法依存信息到原方面术语,提出一种新的方面术语表示方法,利用Glove词向量表示单词以及单词与单词之间的依存关系,构造出包含句法依存信息的依存关系邻接矩阵和依存关系表示矩阵,利用图卷积神经网络和多头注意力机制将句法依存信息融入到方面术语中,使得方面术语表达与上下文结构高度相关。将改进后的方面词术语表示替换到现有模型后,模型泛化能力得到有效提升。对比试验和分析结果表明:该方法具有有效性和泛化性。 相似文献
2.
3.
现场可编程门阵列(FPGA)内部资源众多,其中互连资源出现故障的概率远远高于片内其他资源,而在以往许多互连测试研究中,所生成的测试配置存在无法覆盖反馈桥接故障的难题,所以较难有测试配置实现故障列表的100%覆盖。因此通过约束桥接故障只发生在单个查找表(LUT)内的信号线上,并结合单项函数,对反馈桥接故障模型进行优化改进,从根本上解决难题;然后对优化后的反馈桥接故障设置相应的约束条件,再使用布尔可满足性理论(SAT)生成满足约束条件的测试配置。采用优化后的故障模型对ISCAS"89基准电路进行了测试配置生成实验,结果表明生成的测试向量解决了反馈桥接故障的覆盖难题,并且在实现故障列表的100%覆盖下,优化后的故障模型所需要的测试配置数最少。 相似文献
4.
Xinyu TONG Ziao YU Xiaohua TIAN Houdong GE Xinbing WANG 《Frontiers of Computer Science》2022,16(1):161310
Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice. 相似文献
5.
Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation. 相似文献
6.
7.
Breast cancer is one of the most common types of cancer in women, and histopathological imaging is considered the gold standard for its diagnosis. However, the great complexity of histopathological images and the considerable workload make this work extremely time-consuming, and the results may be affected by the subjectivity of the pathologist. Therefore, the development of an accurate, automated method for analysis of histopathological images is critical to this field. In this article, we propose a deep learning method guided by the attention mechanism for fast and effective classification of haematoxylin and eosin-stained breast biopsy images. First, this method takes advantage of DenseNet and uses the feature map's information. Second, we introduce dilated convolution to produce a larger receptive field. Finally, spatial attention and channel attention are used to guide the extraction of the most useful visual features. With the use of fivefold cross-validation, the best model obtained an accuracy of 96.47% on the BACH2018 dataset. We also evaluated our method on other datasets, and the experimental results demonstrated that our model has reliable performance. This study indicates that our histopathological image classifier with a soft attention-guided deep learning model for breast cancer shows significantly better results than the latest methods. It has great potential as an effective tool for automatic evaluation of digital histopathological microscopic images for computer-aided diagnosis. 相似文献
8.
9.
The International Society for the Study of Vascular Anomalies (ISSVA) provides a classification for vascular anomalies that enables specialists to unambiguously classify diagnoses. This classification is only available in PDF format and is not machine-readable, nor does it provide unique identifiers that allow for structured registration. In this paper, we describe the process of transforming the ISSVA classification into an ontology. We also describe the structure of this ontology, as well as two applications of the ontology using examples from the domain of rare disease research. We used the expertise of an ontology expert and clinician during the development process. We semi-automatically added mappings to relevant external ontologies using automated ontology matching systems and manual assessment by experts. The ISSVA ontology should contribute to making data for vascular anomaly research more Findable, Accessible, Interoperable, and Reusable (FAIR). The ontology is available at https://bioportal.bioontology.org/ontologies/ISSVA. 相似文献
10.