全文获取类型
收费全文 | 574篇 |
免费 | 99篇 |
国内免费 | 8篇 |
专业分类
化学 | 12篇 |
力学 | 6篇 |
综合类 | 7篇 |
数学 | 11篇 |
物理学 | 104篇 |
无线电 | 541篇 |
出版年
2024年 | 28篇 |
2023年 | 56篇 |
2022年 | 88篇 |
2021年 | 97篇 |
2020年 | 86篇 |
2019年 | 71篇 |
2018年 | 34篇 |
2017年 | 22篇 |
2016年 | 12篇 |
2015年 | 7篇 |
2014年 | 10篇 |
2013年 | 16篇 |
2012年 | 11篇 |
2011年 | 9篇 |
2010年 | 8篇 |
2009年 | 9篇 |
2008年 | 17篇 |
2007年 | 15篇 |
2006年 | 13篇 |
2005年 | 14篇 |
2004年 | 8篇 |
2003年 | 11篇 |
2002年 | 6篇 |
2001年 | 7篇 |
2000年 | 13篇 |
1999年 | 2篇 |
1998年 | 2篇 |
1997年 | 3篇 |
1996年 | 1篇 |
1995年 | 1篇 |
1994年 | 2篇 |
1959年 | 2篇 |
排序方式: 共有681条查询结果,搜索用时 0 毫秒
1.
糖尿病视网膜病变(diabetic retinopathy, DR)是一种糖尿病性微血管病变,会在球结膜微血管上有所体现,球结膜血管图像的获取比眼底图像更加便捷,但微血管的特征变化微小且难以量化。为了能够对患者进行早期辅助诊断,本文依据球结膜微血管形态与DR的关联,首先对球结膜图像进行预处理,使用限制对比度自适应直方图均衡(contrast limited adaptive histogram equalization, CLAHE)算法进行图像增强,随机处理使数据增强,然后结合卷积神经网络(convolutional neural network, CNN)和Transformer各自的网络优势构建CTCNet,对处理后的球结膜血管图像进行DR分类,分类准确率达到了97.44%,敏感度97.69%,特异性97.11%,精确度97.69%,通过实验对比CNN和Transformer, CTCNet网络性能优于其他模型,能够有效识别DR。 相似文献
2.
In order to solve the challenging tasks of person re-identification(Re-ID) in occluded scenarios, we propose a novel approach which divides local units by forming high-level semantic information of pedestrians and generates features of occluded parts. The approach uses CNN and pose estimation to extract the feature map and key points, and a graph convolutional network to learn the relation of key points. Specifically, we design a Generating Local Part (GLP) module to divide the feature map into different units. Based on different occluded conditions, the partition mode of GLP has high flexibility and variability. The features of the non-occluded parts are clustered into an intermediate node, and then the spatially correlated features of the occluded parts are generated according to the de-clustering operation. We conduct experiments on both the occluded and the holistic datasets to demonstrate its effectiveness. 相似文献
3.
The technological innovations and wide use of Wireless Sensor Network (WSN) applications need to handle diverse data. These huge data possess network security issues as intrusions that cannot be neglected or ignored. An effective strategy to counteract security issues in WSN can be achieved through the Intrusion Detection System (IDS). IDS ensures network integrity, availability, and confidentiality by detecting different attacks. Regardless of efforts by various researchers, the domain is still open to obtain an IDS with improved detection accuracy with minimum false alarms to detect intrusions. Machine learning models are deployed as IDS, but their potential solutions need to be improved in terms of detection accuracy. The neural network performance depends on feature selection, and hence, it is essential to bring an efficient feature selection model for better performance. An optimized deep learning model has been presented to detect different types of attacks in WSN. Instead of the conventional parameter selection procedure for Convolutional Neural Network (CNN) architecture, a nature-inspired whale optimization algorithm is included to optimize the CNN parameters such as kernel size, feature map count, padding, and pooling type. These optimized features greatly improved the intrusion detection accuracy compared to Deep Neural network (DNN), Random Forest (RF), and Decision Tree (DT) models. 相似文献
4.
铁路接触网绝缘子状态检测对铁路行车安全有着 重大的意义,为解决目前人工对绝缘 子图像检测结果的不确定性,提出一种深度学习结合灰度纹理特征的检测方法。首先使用 Faster R-CNN (faster region-based convolutional neural network)目标检测算法对图像中绝缘子精确识别,再通过灰度共生矩阵对绝缘子纹理 特征进行分析提取,之后结合支持向量机将绝缘子分为正常绝缘子和异常绝缘子,实验数 据结果证明使用能量、熵、相关度3种纹理特征进行绝缘子状态分类时对实验数据中的正 常状态绝缘子的分类精度可达100%,异常状态绝缘子的分类精度达97.5%,最后依据绝缘 子图像灰度分布的周期性特点,利用灰度积分投影将异常绝缘子分为破损绝缘子和夹杂异 物绝缘子。实验结果表明所提方法可以有效对绝缘子状态进行检测分类。 相似文献
5.
LiDAR-based 3D object detection is important for autonomous driving scene perception, but point clouds produced by LiDAR are irregular and unstructured in nature, and cannot be adopted by the conventional Convolutional Neural Networks (CNN). Recently, Graph Convolutional Networks (GCN) has been proved as an ideal way to handle non-Euclidean structure data, as well as for point cloud processing. However, GCN involves massive computation for searching adjacent nodes, and the heavy computational cost limits its applications in processing large-scale LiDAR point cloud in autonomous driving. In this work, we adopt a frustum-based point cloud-image fusion scheme to reduce the amount of LiDAR point clouds, thus making the GCN-based large-scale LiDAR point clouds feature learning feasible. On this basis, we propose an efficient graph attentional network to accomplish the goal of 3D object detection in autonomous driving, which can learn features from raw LiDAR point cloud directly without any conversions. We evaluate the model on the public KITTI benchmark dataset, the 3D detection mAP is 63.72% on KITTI Cars, Pedestrian and Cyclists, and the inference speed achieves 7.9 fps on a single GPU, which is faster than other methods of the same type. 相似文献
6.
为了解决光纤布拉格光栅(FBG)传感网络的光谱信号混叠问题,基于现场可编程门阵列(FPGA)提出了一种利用卷积神经网络(CNN)模型的混叠光谱信号解调算法,并对其进行硬件实现与加速。通过对模型参数进行定点数量化,压缩网络模型的存储空间,提高FPGA中DSP资源的利用率;利用循环展开和数组重排等硬件优化方法,提高了系统实时性,确定了算法的并行计算方案。研究结果表明,在100 MHz的时钟下,测试集解调精度为1.19 pm,推理速度为每帧14.96μs,光谱解调速率为60 kHz,对于FBG混叠光谱信号解调具有较高的精度和速率。 相似文献
7.
8.
Turbo码的编码调制技术 总被引:5,自引:1,他引:5
本文研究了Turbo码与网格编码调制相结合的Turbo码编码调制技术,给出了3种Turbo码与TCM相结合的调制方案,并进行了比较。对方案三进行了计算机模拟,从模拟得到的性能曲线表明,其性能要优于传统的采用卷积码的TCM调制。 相似文献
9.
10.