会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 4. 发明申请
    • LOW-COST FACE RECOGNITION USING GAUSSIAN RECEPTIVE FIELD FEATURES
    • 使用高斯接收场特征的低成本脸部识别
    • WO2016154781A1
    • 2016-10-06
    • PCT/CN2015/075190
    • 2015-03-27
    • INTEL CORPORATIONLI, JianguoCHEN, YurongCHEN, KeCHIU, Ye-Jen
    • LI, JianguoCHEN, YurongCHEN, KeCHIU, Ye-Jen
    • G06K9/00
    • G06K9/00281G06K9/00288G06K9/4619G06K9/6228G06K9/623
    • Methods and systems may provide for facial recognition of at least one input image utilizing hierarchical feature learning and pair-wise classification. Receptive field theory may be used on the input image to generate a pre-processed multi-channel image. Channels in the pre-processed image may be activated based on the amount of feature rich details within the channels. Similarly, local patches may be activated based on the discriminant features within the local patches. Features may be extracted from the local patches and the most discriminant features may be selected in order to perform feature matching on pair sets. The system may utilize patch feature pooling, pair-wise matching,and large-scale training in order to quickly and accurately perform facial recognition at a low cost for both system memory and computation.
    • 方法和系统可以使用分层特征学习和成对分类来提供对至少一个输入图像的面部识别。 可以在输入图像上使用接受场理论来生成预处理的多通道图像。 可以基于频道内的特征丰富的细节的数量来激活预处理图像中的频道。 类似地,可以基于局部补丁内的判别特征激活局部补丁。 可以从局部斑块中提取特征,并且可以选择最多的判别特征,以便在对集上执行特征匹配。 系统可以利用补丁特征池,成对匹配和大规模训练,以便以低成本快速准确地执行系统内存和计算的面部识别。
    • 7. 发明申请
    • IMAGE QUALITY ANALYSIS FOR SEARCHES
    • 图像质量分析
    • WO2013044019A1
    • 2013-03-28
    • PCT/US2012/056558
    • 2012-09-21
    • ALIBABA GROUP HOLDING LIMITEDDENG, YuCHEN, Ke
    • DENG, YuCHEN, Ke
    • G06T7/00
    • G06F17/30256G06F17/3025G06F17/30259G06T7/0002G06T2207/20081G06T2207/30168
    • Image analysis includes: determining, using one or more processors, an image quality score associated with an image, including: determining a foreground and a background in the image; calculating a set of one or more characteristic parameters of the image based on the determined foreground and background; calculating the image quality score based at least in part on the set of characteristic parameters, wherein calculating the image quality score comprises using an image quality computation model that has been pre-trained; and in response to a search query, generating a set of search results that includes a set the images, wherein inclusion of the images or ranking of the search results is based at least in part on image quality scores associated with the set of images.
    • 图像分析包括:确定使用一个或多个处理器与图像相关联的图像质量得分,包括:确定图像中的前景和背景; 基于确定的前景和背景来计算图像的一个或多个特征参数的集合; 至少部分地基于特征参数集来计算图像质量得分,其中计算图像质量得分包括使用已经被预先训练的图像质量计算模型; 并且响应于搜索查询,生成包括设置图像的搜索结果集合,其中包括图像或搜索结果的排序至少部分地基于与该图像集相关联的图像质量得分。