MULTI-CLASS IDENTIFIER, METHOD, AND COMPUTER-READABLE RECORDING MEDIUM
    2.
    发明申请
    MULTI-CLASS IDENTIFIER, METHOD, AND COMPUTER-READABLE RECORDING MEDIUM 有权
    多级标识符,方法和计算机可读记录介质

    公开(公告)号:US20130322743A1

    公开(公告)日:2013-12-05

    申请号:US13904911

    申请日:2013-05-29

    CPC classification number: G06K9/6227 G06K9/6256 G06K9/6281

    Abstract: A multi-class identifier identifies a kind of an imager, and identifies in detail with respect to a specified kind of a group. The multi-class identifier includes: an identification fault counter providing the image for test that includes any of class labels to the kind identifiers so that the kind identifiers individually identify the kind of the provided image, and counting, for a combination of arbitrary number of kinds among the plurality of kinds, the number of times of incorrect determination in the arbitrary number of kinds that belongs to the combination; a grouping processor, for a group of the combination for which count result is equal to or greater than a predetermined threshold, adding a group label corresponding to the group to the image for learning that includes the class label corresponding to any of the arbitrary number of kinds that belongs to the group.

    Abstract translation: 多类标识符识别一种成像器,并且相对于指定类型的组来详细识别。 多类标识符包括:提供测试图像的识别故障计数器,其包括类型标识符的任何类别标签,以便种类标识符单独地识别所提供的图像的种类,并且对于任意数量的 多种种类,属于组合的任意种类的不正确确定次数; 分组处理器,对于其计数结果等于或大于预定阈值的组合组,将与该组相对应的组标签与用于学习的图像相加,所述组标签包括与任意数量 属于该组的种类。

    MACHINE LEARNING DEVICE AND CLASSIFICATION DEVICE FOR ACCURATELY CLASSIFYING INTO CATEGORY TO WHICH CONTENT BELONGS
    5.
    发明申请
    MACHINE LEARNING DEVICE AND CLASSIFICATION DEVICE FOR ACCURATELY CLASSIFYING INTO CATEGORY TO WHICH CONTENT BELONGS 有权
    机器学习设备和分类设备,用于精确分类到类别中,包含内容

    公开(公告)号:US20160125273A1

    公开(公告)日:2016-05-05

    申请号:US14850516

    申请日:2015-09-10

    CPC classification number: G06K9/6269 G06K9/4676 G06K9/6234

    Abstract: An image acquisition unit of a machine learning device acquires n learning images assigned with labels to be used for categorization (n is a natural number larger than or equal to 2). A feature vector acquisition unit acquires a feature vector representing a feature from each of the n learning images. A vector conversion unit converts the feature vector for each of the n learning images to a similarity feature vector based on a similarity degree between the learning images. A classification condition learning unit learns a classification condition for categorizing the n learning images, based on the similarity feature vector converted by the vector conversion unit and the label assigned to each of the n learning images. A classification unit categorizes unlabeled testing images in accordance with the classification condition learned by the classification condition learning unit.

    Abstract translation: 机器学习装置的图像获取单元获取分配有用于分类的标签的n个学习图像(n是大于或等于2的自然数)。 特征向量获取单元从n个学习图像中获取表示特征的特征向量。 向量转换单元基于学习图像之间的相似度将n个学习图像中的每一个的特征向量转换为相似特征向量。 分类条件学习单元基于由向量转换单元转换的相似特征向量和分配给每个n个学习图像的标签来学习用于对n个学习图像进行分类的分类条件。 分类单元根据分类条件学习单元学习的分类条件对未标记的测试图像进​​行分类。

    IMAGE CAPTURING APPARATUS CAPABLE OF CAPTURING PANORAMIC IMAGE
    7.
    发明申请
    IMAGE CAPTURING APPARATUS CAPABLE OF CAPTURING PANORAMIC IMAGE 有权
    拍摄全景图像的图像捕获设备

    公开(公告)号:US20150130895A1

    公开(公告)日:2015-05-14

    申请号:US14601991

    申请日:2015-01-21

    Abstract: A digital camera includes an image capturing unit, an image composition unit, and a display control unit. The image capturing unit captures frames at predetermined time intervals. The image composition unit sequentially combines at least a part of image data from image data of a plurality of frames sequentially captured by the image capturing unit at predetermined time intervals. The display control unit performs control to sequentially display image data combined by the image composition unit while the image data of the frames are captured by the image capturing unit at predetermined time intervals.

    Abstract translation: 数码相机包括图像拍摄单元,图像合成单元和显示控制单元。 图像捕获单元以预定的时间间隔捕获帧。 图像合成单元以预定的时间间隔顺序地组合由图像捕获单元顺序捕获的多个帧的图像数据的图像数据的至少一部分。 显示控制单元执行控制以顺序地显示由图像合成单元组合的图像数据,同时以预定时间间隔由图像捕获单元捕获帧的图像数据。

    MULTI-CLASS DISCRIMINATING DEVICE
    8.
    发明申请
    MULTI-CLASS DISCRIMINATING DEVICE 有权
    多级识别装置

    公开(公告)号:US20140119646A1

    公开(公告)日:2014-05-01

    申请号:US14063311

    申请日:2013-10-25

    CPC classification number: G06K9/6281 G06K9/6234 G06K9/6256 G06K9/6292

    Abstract: A multi-class discriminating device for judging to which class a feature represented by data falls. The device has a first unit for generating plural first hierarchical discriminating devices for discriminating one from N, and a second unit for combining score values output respectively from the plural first hierarchical discriminating devices to generate a second hierarchical feature vector and for entering the second hierarchical feature vector to generate plural second hierarchical discriminating devices for discriminating one from N. When data is entered, the plural first hierarchical discriminating devices output score values, and these score values are combined together to generate the second hierarchical feature vector. When the second hierarchical feature vector is entered, the second hierarchical discriminating device which outputs the maximum score value is selected. The class corresponding to the selected second hierarchical discriminating device is discriminated as the class, into which the feature represented by the entered data falls.

    Abstract translation: 一种用于判断由数据表示的特征属于哪个类的多类鉴别装置。 该装置具有第一单元,用于产生用于从N中识别的多个第一分级鉴别装置,以及用于组合分别从多个第一层次鉴别装置输出的分数值的第二单元,以产生第二分层特征向量,并用于输入第二分层特征 生成多个用于从N中识别的第二层次鉴别装置。当输入数据时,多个第一层次鉴别装置输出得分值,并将这些得分值组合在一起以产生第二层次特征向量。 当输入第二层次特征向量时,选择输出最大得分值的第二层次鉴别装置。 对应于所选择的第二层次鉴别装置的类别被鉴别为由输入的数据表示的特征落入的类别。

    IMAGE PROCESSING DEVICE THAT DISPLAYS RETRIEVED IMAGE SIMILAR TO TARGET IMAGE
    9.
    发明申请
    IMAGE PROCESSING DEVICE THAT DISPLAYS RETRIEVED IMAGE SIMILAR TO TARGET IMAGE 有权
    图像处理设备,显示将类似图像恢复到目标图像

    公开(公告)号:US20130251253A1

    公开(公告)日:2013-09-26

    申请号:US13847673

    申请日:2013-03-20

    CPC classification number: G06F17/30247 G06F17/3025 G06F17/30259

    Abstract: The image acquisition unit 41 acquires an image including an object. By comparing information related to the shape of a relevant natural object that is included as the object in the target image acquired by the image acquisition unit 41, and information related to respective shapes of a plurality of types prepared in advance, at least one flower type for the natural object in question is selected. The secondary selection unit 43 then selects data of a representative image from among data of a plurality of images of different color, of the same flower type as prepared in advance, for each of at least one flower type selected by the primary selection unit 42, based on information related to color of the relevant natural object included as the object in the image acquired by the image acquisition unit 41.

    Abstract translation: 图像获取单元41获取包括对象的图像。 通过将与由图像获取单元41获取的目标图像中包括的作为对象的相关自然物体的形状相关的信息与预先准备的多种类型的各种形状相关的信息进行比较,至少一种花型 对于所讨论的自然对象是选择的。 次要选择单元43然后从由主要选择单元42选择的至少一种花型中的每一种,从与预先制作的相同花型的不同颜色的多个图像的数据中选择代表图像的数据, 基于与由图像获取单元41获取的图像中包括的对象相关的相关自然对象的颜色相关的信息。

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