convolutionalneuralNetwork相关论文
Machine learning approach for label-free rapid detection and identification of virus using Raman spe
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Deep learning has recently been progressively introduced into the field of modulation classification due to its wide app......
Convolutional Neural Networks (CNN) have achieved great success in many computer vision tasks.However,it is difficult to......
With the rapid development of Internet of Things (IoT) technologies,the detection and analysis of malware have become a ......
The massive number of sensors deployed in the Internet of Things (IoT) produce gigantic amounts of data for facilitating......
Taking Jiuhong Modern Agriculture Demonstration Park of Heilongjiang Province as the base for rice disease image acquisi......
Computational ghost imaging[CGI]has recently been intensively studied as an indirect imaging technique.However,the image......
Complicated radio resource management, e.g., handover condition, will trouble the user in non-terrestrial networks due t......
Fast recognition using convolutional neural network for the coal particle density range based on ima
A method based on multiple images captured under different light sources at different incident angles was developed to r......
Acupuncture enhances brain function in patients with mild cognitive impairment: evidence from a func
Mild cognitive impairment (MCI) is a precursor to Alzheimer\'s disease. It is imperative to develop a proper treatment......
Directly grasping the tightly stacked objects may cause collisions and result in failures, degenerating the functionalit......
Although considerable success has been achieved in urban air quality prediction (AQP) with machine learning techniques,a......
As an important technique for managing and maintaining civil infrastructure,structural health monitoring(SHM)has been ap......
Pavement friction and texture characteristics are important to road surface safety.Despite extensive studies conducted i......
We present a practical approach to vehicle detection at container terminals based on a single camera and prevailing conv......
As an essential sub-task of frame-semantic parsing,Frame Identifica-tion(FI)is a fundamentally important research topic ......
This paper presents an automatic grayscale image colorization method using convolutional neural network.Besides the gray......
Smart watches have become one of the most representative devices in wearable devices because of their unique advantages ......
随着视频技术的飞速发展,越来越多的视频应用逐步进入人们的生活中,因此对视频质量的研究很有意义。基于卷积神经网络和循环神经网......
针对计算机视觉中目标跟踪的问题,提出基于卷积神经网络(CNN)提取深度特征并与边缘特征进行自适应融合的策略来实现视频目标的跟踪......
对视网膜血管形态特征的分析有助于视网膜相关疾病的诊断。为了能够更准确地分割出视网膜血管,提出一种基于双流网络的分割视网膜......
针对目前算法对遥感图像中背景复杂、目标小而密集的复杂场景下的目标检测精度低的问题,提出了一种基于YOLOv3的改进算法,在YOLOv3......
针对低照度应用场景,提出一种基于卷积神经网络的可见光与近红外融合算法,采用端到端网络实现了图像融合,所得融合图像能够兼顾近......
针对现有主流检测算法在低光照或光照条件强烈变化情况下对交通标志检测精度不足、漏检现象严重的问题,提出一种改进后的基于图像......
无人机搜索和识别目标依赖于目标检测算法的快速性和准确性。针对经典目标检测算法的网络结构复杂、计算机性能要求高和目标检测速......
为解决人脸表情识别任务中存在的类内表情差异性大、类间表情相似度高的问题,基于传统的Softmax损失函数和Island损失函数,提出一......
提出基于卷积神经网络的驾驶行为分析算法,该算法在人脸定位的基础上实现了驾驶员的疲劳检测和行为检测。针对疲劳检测任务,探究了......
A measurement of epidermal thickness of fingertip skin from OCT images using convolutional neural ne
In this study, we proposed a method to measure the epidermal thickness (ET) of skin based on deep convolutional neural n......
针对监控视频中的多尺度近岸舰船检测问题,提出了一种基于特征重聚焦网络的舰船目标检测算法,设计了由多维特征聚合模块(MFAM)与注......
提出了一种基于卷积神经网络(CNN)的数字散斑图像位移场测量方法。采用给定多种变形模式的精确位移场系列数字散斑图像构建数据集,......
植物群落结构的改变是草原退化的主要特征之一,草原草种类识别与分类是基于遥感的草原退化评价与研究的基础。荒漠化草原物种混杂......
提出了一种基于集成卷积神经网络(CNN)的遥感影像场景分类算法。通过构建反向传播网络实现了场景图像的复杂度度量;根据图像的复杂......
大部分基于卷积神经网络的双目立体匹配算法往往将双目图像对的像素级别特征作为匹配代价进行计算,缺乏将全局特征信息结合到立体......
基于注意力机制的神经网络可重点提取样本中关键区域的特征信息,将此特点应用于偏振图像目标分类任务中有助于充分获取不同偏振图......
为使通过卷积神经网络学习到的人脸识别特征更容易判别,在角度距离损失函数A-Softmax的基础上进行改进,将人脸属性融入到训练过程......
提出了一种基于卷积神经网络和XGBoost的摔倒检测算法。采用基于squeeze-and-excitation模块的YOLO-v3算法对图片进行人体区域检测......
目前,基于统计先验的图像去模糊方法对噪声敏感,细节恢复能力有限,而基于先验学习的算法对图像及其模糊类型、噪声水平等适应性较......
建立了室内人员检测数据集(IHDD),提出了基于联合学习的多视角室内人员检测网络模型(MVNN)。该模型由输入数据层、特征提取层、可......
针对卷积神经网络巨大的计算量和存储量导致其难以应用于嵌入式终端设备的难题,提出了一种基于灰色关联分析的模型裁剪方法。利用......
面对当前复杂场景下异常事件检测算法过度依赖帧级别标记,以及I3D模型耗时长、内存占用大等问题,设计了一种基于I3D的M-I3D模型并......
针对先进驾驶辅助系统对车辆前视景深信息的需求,在无监督学习框架下提出了一种基于单目视觉的场景深度估计方法。为了降低不同尺......
全天时天文导航图像是在大气层内白天的条件下拍摄,因此图像具有强背景,低信噪比等特点,传统星点提取算法对图像星点的提取效果较......
基于改进的深度残差网络(ResNet),提出更加适合肺部组织的计算断层扫描(CT)图像模式分类模型。为克服医学图像分析中可用数据集稀......
点云作为一种重要的3D数据类型,随着3D采集技术的发展已被广泛用于多个应用场景。深度学习因其处理大型数据集的高效性、提取特征......
对于基于深度学习的立体匹配而言,模型的网络结构对算法精度的影响很大,而算法运行效率也是实际应用中需要考虑的重要因素。提出一......
提出了一种结合级联的区域建议网络和检测网络的遥感图像机场检测方法。通过改进区域建议网络,以获得高质量的机场建议框;通过改进......
提出了一种基于级联的2.5维(2.5D)卷积神经网络。将该任务拆分为脑肿瘤整体分割、肿瘤核分割、增强肿瘤分割三个子任务,并将三个结......
Computational ghost imaging(CGI) has recently been intensively studied as an indirect imaging technique. However, the im......
中国象棋棋子定位采用的传统图像处理方法,复杂度高;识别棋子采用的传统文字识别方法,泛化性较差、精确度较低。提出一种基于棋子......
基于卷积神经网络模型,提出一种立体图像舒适度评价方法。该方法无须提前根据特定的任务从图像中人工提取具体的特征,而是模拟人脑......
