搜索结果: 1-15 共查到“S-CNN”相关记录35条 . 查询时间(0.062 秒)
一种面向移动端的浅层CNN表情识别
面部表情识别 卷积神经网络 全局平均池化 GoogleColab CoreML
2022/3/15
融合CNN和MRF的激光点云层次化语义分割方法
激光点云 语义分割 层次化提取 残差学习 马尔可夫随机场(MRF)
2021/3/30
三维点云语义分割的结果包含着对场景中多个目标的识别,是三维场景信息提取的重要环节,在智慧城市等多个领域扮演关键角色。由于三维激光点云数据量庞大、场景复杂性高等问题,大多数现有方法只能以相对较低的识别率提取有限类型的对象。本文提出了一种在三维激光点云场景中结合残差学习和马尔可夫随机场(MRF)优化的层次化多类型目标自动提取框架。该框架首先将点云滤波为地面点和非地面点;然后从非地面点中提取建筑物以降低...
基于关键词策略和CNN的中文文本有害信息分类
词向量 分词频文档频率 特征词集合 Word2Vec模型 卷积神经网络
2022/3/23
以宁夏16套枸杞农田实景监测系统2018年和2019年拍摄的图像作为资料,结合枸杞开花期和果实成熟期的植物学特征,利用更快速的基于区域的卷积神经网络(Faster R-CNN)方法对图像进行训练、分类,构建枸杞开花期和果实成熟期的识别算法,以平均精确率(AP)和平均精度均值(mAP)作为模型的评价指标,并将自动识别结果与专家目视判断结果和田间观测记录进行对比。结果表明:当网络结构中重要超参数批尺寸...
基于Mask R-CNN的枪弹底火装配质量检测系统设计
底火 装配质量检测 Mask RCNN 机器视觉
2020/8/17
提出了一种基于Mask R-CNN的枪弹底火装配质量检测方案。构建了底火装配质量在线检测系统,该系统利用机器视觉技术设计了基于Mask R-CNN网络模型的检测算法,主要借助目标检测算法 Faster R-CNN进行目标定位,用全卷积神经网络(FCN) 进行分割,实现枪弹底火装配缺陷位置显示和标记。通过实验将本文检测方法与人工检测方式进行了对比,结果表明,该方案能够快速、准确、有效地判别出合格品,...
提出了一种深度卷积神经网络与极限学习机相结合的滚动轴承自适应故障诊断方法。该方法的第一阶段训练深度卷积神经网络作为特征提取器:通过卷积层和池化层提取低阶特征,然后在全连接层合成高层次特征。第二阶段将第一阶段自适应提取出来的特征通过极限学习机进行轴承故障类别的准确快速分类,实现了自适应“端到端”的故障诊断。实验结果表明,该方法能有效的识别故障类别,缩短了训练时间,并具有良好的鲁棒性和实时性。
Methodology for Efficient CNN Architectures in Profiling Attacks
Side-Channel Attacks Deep Learning Architecture
2019/7/15
The side-channel community has recently investigated a new approach, based on deep learning, to significantly improve profiled attacks against embedded systems. Previous works have shown the benefit o...
基于Faster R-CNN的实木板材缺陷检测识别系统
实木板材 板材缺陷识别 深度学习 Faster R-CNN 无损检测
2020/7/31
我国木材资源有限,为了提高木材的利用率,采用机器视觉来实现木材缺陷快速而稳定的检测,不仅可以克服人工检测的低效率和木材缺陷识别的低准确率,而且对提高木材加工企业的智能化水平具有重要意义。为了高效、快速、准确地进行无损检测,采用深度学习方法,建立了一种基于快速深度神经网络的实木板材缺陷识别模型。
The AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data with GPUs
Fully Homomorphic Encryption Deep Learning Encrypted CNN
2018/11/2
Fully homomorphic encryption, with its widely-known feature of computing on encrypted data, empowers a wide range of privacy-concerned cloud applications including deep learning as a service. This com...
RESEARCH ON HIGH ACCURACY DETECTION OF RED TIDE HYPERSPECRRAL BASED ON DEEP LEARNING CNN
Red Tide CNN Hyperspectral Remote Sensing Glint
2018/5/14
Increasing frequency in red tide outbreaks has been reported around the world. It is of great concern due to not only their adverse effects on human health and marine organisms, but also their impacts...
A CLOUD BOUNDARY DETECTION SCHEME COMBINED WITH ASLIC AND CNN USING ZY-3, GF-1/2 SATELLITE IMAGERY
CNN ASLIC GF-1/2 ZY-3 Imaging platforms
2018/5/14
Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method bas...
FUSING PANCHROMATIC AND SWIR BANDS BASED ON CNN – A PRELIMINARY STUDY OVER WORLDVIEW-3 DATASETS
Pan-sharpening, Convolutional Neural Network, Short-wave Infrared, Deep Learning, Image fusion, Remote Sensing
2018/5/14
The traditional fusion methods are based on the fact that the spectral ranges of the Panchromatic (PAN) and multispectral bands (MS) are almost overlapping. In this paper, we propose a new pan-sharpen...