全文获取类型
收费全文 | 9329篇 |
免费 | 2369篇 |
国内免费 | 1571篇 |
专业分类
电工技术 | 312篇 |
综合类 | 918篇 |
化学工业 | 51篇 |
金属工艺 | 96篇 |
机械仪表 | 565篇 |
建筑科学 | 85篇 |
矿业工程 | 54篇 |
能源动力 | 34篇 |
轻工业 | 185篇 |
水利工程 | 43篇 |
石油天然气 | 57篇 |
武器工业 | 58篇 |
无线电 | 1886篇 |
一般工业技术 | 579篇 |
冶金工业 | 53篇 |
原子能技术 | 14篇 |
自动化技术 | 8279篇 |
出版年
2024年 | 97篇 |
2023年 | 291篇 |
2022年 | 452篇 |
2021年 | 518篇 |
2020年 | 542篇 |
2019年 | 365篇 |
2018年 | 323篇 |
2017年 | 412篇 |
2016年 | 470篇 |
2015年 | 505篇 |
2014年 | 699篇 |
2013年 | 620篇 |
2012年 | 833篇 |
2011年 | 891篇 |
2010年 | 752篇 |
2009年 | 753篇 |
2008年 | 800篇 |
2007年 | 778篇 |
2006年 | 644篇 |
2005年 | 570篇 |
2004年 | 440篇 |
2003年 | 381篇 |
2002年 | 245篇 |
2001年 | 182篇 |
2000年 | 139篇 |
1999年 | 121篇 |
1998年 | 87篇 |
1997年 | 56篇 |
1996年 | 43篇 |
1995年 | 40篇 |
1994年 | 29篇 |
1993年 | 22篇 |
1992年 | 23篇 |
1991年 | 13篇 |
1990年 | 8篇 |
1989年 | 15篇 |
1988年 | 10篇 |
1987年 | 7篇 |
1986年 | 7篇 |
1985年 | 14篇 |
1984年 | 10篇 |
1983年 | 13篇 |
1982年 | 10篇 |
1981年 | 10篇 |
1980年 | 11篇 |
1979年 | 3篇 |
1978年 | 4篇 |
1977年 | 5篇 |
1972年 | 1篇 |
1959年 | 1篇 |
排序方式: 共有10000条查询结果,搜索用时 15 毫秒
991.
Diabetic retinopathy (DR) is the major ophthalmic pathological cause for loss of eye sight due to changes in blood vessel structure. The retinal blood vessel morphology helps to identify the successive stages of a number of sight threatening diseases and thereby paves a way to classify its severity. This paper presents an automated retinal vessel segmentation technique using neural network, which can be used in computer analysis of retinal images, e.g., in automated screening for diabetic retinopathy. Furthermore, the algorithm proposed in this paper can be used for the analysis of vascular structures of the human retina. Changes in retinal vasculature are one of the main symptoms of diseases like hypertension and diabetes mellitus. Since the size of typical retinal vessel is only a few pixels wide, it is critical to obtain precise measurements of vascular width using automated retinal image analysis. This method segments each image pixel as vessel or nonvessel, which in turn, used for automatic recognition of the vasculature in retinal images. Retinal blood vessels are identified by means of a multilayer perceptron neural network, for which the inputs are derived from the Gabor and moment invariants-based features. Back propagation algorithm, which provides an efficient technique to change the weights in a feed forward network is utilized in our method. The performance of our technique is evaluated and tested on publicly available DRIVE database and we have obtained illustrative vessel segmentation results for those images. 相似文献
992.
993.
The scanning electron microscopy (SEM) images are commonly used to understand the microstructure of the concrete. With the advancements in the field of computer vision, many researchers have adopted the image processing technique for the microstructure analysis. Most of the previous methods are not adaptable, non-reproducible, semi-automated, and most importantly all these methods are highly influenced by image magnification. Therefore, to overcome these challenges, this paper presents a machine learning based image segmentation method for microstructure analysis and degree of hydration measurement using SEM images. In addition, the authors looked into the impact of magnification of SEM images on the model accuracy and classifier training for the degree of hydration measurement considering two scenarios. First, the image segmentation was performed using a classifier of specific magnification, and then a common classifier is trained using the image of different magnification. The results show that the Random Forest classifier algorithm is suitable for microstructure analysis using SEM images. Through the statistical analysis, it has been proved that there is no significant effect of magnification on model training and accuracy for the degree of hydration measurement. So, a single classifier can be used to process the images of different magnification of a specimen which reduces the effort of training and computational time. The proposed method can generate highly accurate and reliable results in a shorter time and lower cost. Moreover, the findings in this research can be useful for researchers to determine the optimum magnification required for the microstructure analysis. 相似文献
994.
995.
996.
Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. New insights into the pathogenesis of this lethal disease are urgently needed. Chromosomal copy number alterations (CNAs) can lead to activation of oncogenes and inactivation of tumor suppressors in human cancers. Thus, identification of cancer-specific CNAs will not only provide new insight into understanding the molecular basis of tumor genesis but also facilitate the identification of HCC biomarkers using CNA. 相似文献
997.
An adaptive color similarity function suitable for image segmentation and its numerical evaluation 下载免费PDF全文
Rodolfo Alvarado‐Cervantes Edgardo M. Felipe‐Riverón Vladislav Khartchenko Oleksiy Pogrebnyak 《Color research and application》2017,42(2):156-172
In this article, we present an adaptive color similarity function defined in a modified hue‐saturation‐intensity color space, which can be used directly as a metric to obtain pixel‐wise segmentation of color images among other applications. The color information of every pixel is integrated as a unit by an adaptive similarity function thus avoiding color information scattering. As a direct application we present an efficient interactive, supervised color segmentation method with linear complexity respect to the number of pixels of the input image. The process has three steps: (1) Manual selection of few pixels in a sample of the color to be segmented. (2) Automatic generation of the so called color similarity image (CSI), which is a gray level image with all the gray level tonalities associated with the selected color. (3) Automatic threshold of the CSI to obtain the final segmentation. The proposed technique is direct, simple and computationally inexpensive. The evaluation of the efficiency of the color segmentation method is presented showing good performance in all cases of study. A comparative study is made between the behavior of the proposed method and two comparable segmentation techniques in color images using (1) the Euclidean metric of the a* and b* color channels rejecting L* and (2) a probabilistic approach on a* and b* in the CIE L*a*b* color space. Our testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. It was obtained from the results that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume in the CIE L*a*b* color space. We show that our solution improves the quality of the proposed color segmentation technique and its quick result is significant with respect to other solutions found in the literature. The method also gives a good performance in low chromaticity, gray level and low contrast images. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 156–172, 2017 相似文献
998.
999.
Deep learning has gained a significant popularity in recent years thanks to its tremendous success across a wide range of relevant fields of applications, including medical image analysis domain in particular. Although convolutional neural networks (CNNs) based medical applications have been providing powerful solutions and revolutionizing medicine, efficiently training of CNNs models is a tedious and challenging task. It is a computationally intensive process taking long time and rare system resources, which represents a significant hindrance to scientific research progress. In order to address this challenge, we propose in this article, R2D2, a scalable intuitive deep learning toolkit for medical imaging semantic segmentation. To the best of our knowledge, the present work is the first that aims to tackle this issue by offering a novel distributed versions of two well-known and widely used CNN segmentation architectures [ie, fully convolutional network (FCN) and U-Net]. We introduce the design and the core building blocks of R2D2. We further present and analyze its experimental evaluation results on two different concrete medical imaging segmentation use cases. R2D2 achieves up to 17.5× and 10.4× speedup than single-node based training of U-Net and FCN, respectively, with a negligible, though still unexpected segmentation accuracy loss. R2D2 offers not only an empirical evidence and investigates in-depth the latest published works but also it facilitates and significantly reduces the effort required by researchers to quickly prototype and easily discover cutting-edge CNN configurations and architectures. 相似文献
1000.
This paper presents a novel image segmentation algorithm driven by human visual system (HVS) properties. Segmentation quality metrics, based on perceptual properties of HVS with respect to segmentation, are integrated into an energy function. The energy function encodes the HVS properties from both region-based and boundary-based perspectives, where the just-noticeable difference (JND) model is employed when calculating the difference between the image contents. Extensive experiments are carried out to compare the performances of three variations of the presented algorithm and several representative segmentation and clustering algorithms available in the literature. The results show superior performance of our approach. 相似文献