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1.
针对目前工业CT图像转换为3D打印G代码方法效率低的问题,提出一种基于邻层数据匹配的工业CT图像直接转换成G代码的方法。首先采用Canny算子提取工业CT图像的轮廓,然后处理轮廓分叉问题,实现邻层间几何信息数据匹配,其次进行邻层间轮廓插值以满足3D打印层间厚度要求,从而避免"阶梯效应",最后通过填充编码得到用于3D打印的G代码。使用本文提出的方法,轮毂CT图像转换为G代码的时间为10.5 s,耗时远小于其他间接转换方法;3D打印出的轮毂无"阶梯效应",平均尺寸误差率为0.25%。实验结果表明,该方法不涉及中间格式,转换效率高,转换误差与传统方法相当,适用于具有复杂内腔结构的零件。  相似文献   
2.
Micro-milling is an extensively used micro-machining process for producing high precision 3D components from varied materials. However, tool wear in micro-tools is a big concern, as component accuracy directly depends on it. Also, size effects limit the monitoring by the naked eye, but it can be compensated by implying a proper wear monitoring mechanism. Various direct and indirect methods have earlier been used for monitoring purposes, and considering the needs of the fourth industrial revolution, one of the direct methods, machine vision, when combined with image processing algorithms, can play a more prominent role. Current work focuses on creating a wear monitoring algorithm based on fuzzy c-means clustering technique directly implied on acquired colour micro-tool images. The proposed algorithm has three steps: the first step is Region of Interest (ROI) extraction, where the background is removed, orientation correction is done, and ROI on each tooth is extracted from micro-tool colour images. The second uses the fuzzy c-means technique on ROI to cluster them, from which wear cluster is chosen and morphologically enhanced. The last step performs pixel level measurement and results in numerical wear width. Overall, quantitative results at each step are correlation coefficient of 99 % after image registration, segmentation accuracy of 92 % and wear measurement accuracy of 97 %. A comparison is also made between the proposed algorithm, k-means clustering and RGB thresholding technique, where the proposed algorithm outshines. Lastly, the wear measurement error of the proposed algorithm is less than 5 %, indicating its repeatable, reliable, and robust nature.  相似文献   
3.
Recently, single image super-resolution (SISR) has been widely applied in the fields of underwater robot vision and obtained remarkable performance. However, most current methods generally suffered from the problem of a heavy burden on computational resources with large model sizes, which limited their real-world underwater robotic applications. In this paper, we introduce and tackle the super resolution (SR) problem for underwater robot vision and provide an efficient solution for near real-time applications. We present a novel lightweight multi-stage information distillation network, named MSIDN, for better balancing performance against applicability, which aggregates the local distilled features from different stages for more powerful feature representation. Moreover, a novel recursive residual feature distillation (RRFD) module is constructed to progressively extract useful features with a modest number of parameters in each stage. We also propose a channel interaction & distillation (CI&D) module that employs channel split operation on the preceding features to produce two-part features and utilizes the inter channel-wise interaction information between them to generate the distilled features, which can effectively extract the useful information of current stage without extra parameters. Besides, we present USR-2K dataset, a collection of over 1.6K samples for large-scale underwater image SR training, and a testset with an additional 400 samples for benchmark evaluation. Extensive experiments on several standard benchmark datasets show that the proposed MSIDN can provide state-of-the-art or even better performance in both quantitative and qualitative measurements.  相似文献   
4.
为解决太赫兹(Terahertz,THz)图像内泊松高斯混合噪声导致芳纶纤维蜂窝材料脱粘缺陷轮廓检测精度低的问题,基于Anscombe变换与小波阈值法构建了THz图像降噪模型。高斯噪声方差为降噪模型的必要参数,但实际THz图像噪声分布未知,且噪声与纹理在高频混叠,给方差准确估计提出了挑战。为此,首先以样件纹理几何形状为先验信息,构造Benzene-ring算子去除THz图像纹理,使其小波域高频分量中仅含有噪声;然后提出改进的Logistic混沌映射提高样本集的多样性,以训练Elman神经网络准确建立高频分量与高斯噪声方差间映射关系;最后依据噪声方差估计值,基于Anscombe变换将泊松高斯混合噪声转化为高斯噪声,并利用小波阈值法与Anscombe逆变换得到了最终THz降噪图像。仿真与试验结果表明,所提出的方法降噪效果最佳并有效提高缺陷轮廓检测精度,相比于高斯滤波、小波阈值以及非局部均值法,平均梯度指标分别提升12%、33%、9%,缺陷面积绝对误差分别降低234 mm2、304 mm2、263 mm2。  相似文献   
5.
《Ceramics International》2021,47(21):29908-29918
The cellulose derived carbon/graphene/ZnO aerogel composite was prepared as an electrode in order to investigate the electrochemical properties. Carbon aerogel was synthesized using paper as an available cellulose source, and the composite was obtained through a new and simple preparation method including the immersion of monolithic carbon aerogel in graphene oxide/Zn2+ suspension and subsequent chemical reduction and freeze drying. The morphology, functional groups and crystalline structure of the samples were studied with Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Diffraction Spectroscopy (XRD), respectively. Electrochemical performance of the prepared binder free electrodes was examined using Cyclic Voltammetry (CV), Galvanostatic Charge-Discharge (GCD) and Electrochemical Impedance Spectroscopy (EIS). The data revealed that flexible carbon/graphene/ZnO composite resulted in a low density (0.035 g cm−3) electrode with the capacitance of 900 mF cm−2 at a high current density of 10 mA cm−2, lower IR drop and high cyclic stability (capacitance retention of 96%) after 1000 cycles, at 10 mA cm−2. These features were due to the presence of 3D porous conductive network, highly reduced graphene oxide, and the formation of ZnO nanoparticles on graphene sheets. Moreover, polyaniline (PANI) was introduced to carbon/graphene/ZnO composite electrode using electro-oxidation method at different reaction time and aniline concentration in order to achieve remarkably improved capacitance of 2500 mF cm−2 (at 10 mA cm−2) and low charge transfer resistance. Also, after the supercapacitor device assembly, the capacitance was retained. Based on the results, the synthesized composite is a promising material for new generation of lightweight freestanding electrodes with the high electrochemical performance.  相似文献   
6.
In order to determine the effect of heat treatment on the mechanical and wear properties of Zn–40Al– 2Cu–2Si alloy, different heat treatments including homogenization followed by air-cooling (H1), homogenization followed by furnace-cooling (H2), stabilization (T5) and quench–aging (T6 and T7) were applied. The effects of these heat treatments on the mechanical and tribological properties of the alloy were studied by metallography and, mechanical and wear tests in comparison with SAE 65 bronze. The wear tests were performed using a block on cylinder type test apparatus. The hardness, tensile strength and compressive strength of the alloy increase by the application of H1 and T6 heat treatments, and all the heat treatments except T6, increase its elongation to fracture. H1, T5 and T6 heat treatments cause a reduction in friction coefficient and wear volume of the alloy. However, this alloy exhibits the lowest friction coefficient and wear volume after T6 heat treatment. Therefore, T6 heat treatment appears to be the best process for the lubricated tribological applications of this alloy at a pressure of 14 MPa. However, Zn–40Al–2Cu–2Si alloy in the as-cast and heat-treated conditions shows lower wear loss or higher wear resistance than the bronze.  相似文献   
7.
采用风景园林学与人工智能的跨学科研究方式,开发了一种将深度学习模型——生成对抗网络(Generative Adversarial Network,GAN)用于风景园林平面图用地识别与图像渲染的新应用场景。以325张细致标注的平面方案图建立用于深度学习的数据集,训练循环生成对抗网络(CycleGAN)实现平面图不同用地类型地块的提取任务,以及平面色块图到色彩肌理图的渲染生成。进一步从图片质量、正确规范性和色彩表达等方面评价模型的识别与渲染结果。该训练模型有潜力被应用于风景园林案例的用地类型分析及平面渲染,帮助设计师提升分析及制图效率。  相似文献   
8.
将小波变换多尺度理论用于分析确定共生矩阵最佳步长参数值,利用小波变换对原始图像进行分解,根据具体纹理图像,选择合适小波子图像(近似图像或其细节子图像)进行纹理分析,通过计算分解图像的纹理特征参数(对比度)确定最佳步长参数。当步长参数为最优值时,计算所得纹理特征参数值将处于周期极值位置,其利于纹理分析。相对于原始图像,分解图像数据量小,在寻优共生矩阵最佳步长参数时,计算复杂度及时间消耗都有所降低。实验验证,基于小波分解图像所得最佳步长参数值是精确的。  相似文献   
9.
提出了一种基于红外检测的变电站设备热状态诊断方案。首先基于变电站设备的红外图像,采用局部方差映射函数和遗传算法阈值提取了变电站设备的热状态数据,以用于对异常区域进行分割。然后构建了红外图像灰度数与变电站设备温度两者之间的关系。最后采用改进的相对温差法达到了对设备热状态进行分类和诊断的目标,并捕获定位了变电站设备的热状态异常区域。实验结果表明,该方法提高了异常热区提取的精度和效率,提升了变电站设备热状态诊断的容错能力,进一步保证了变电站和整个电力系统的运行稳定性。  相似文献   
10.
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