SYSTEM AND METHOD FOR PROVIDING MODULAR ONLINE PRODUCT SELECTION,
VISUALIZATION AND DESIGN SERVICES
    2.
    发明申请
    SYSTEM AND METHOD FOR PROVIDING MODULAR ONLINE PRODUCT SELECTION, VISUALIZATION AND DESIGN SERVICES 审中-公开
    提供模块化在线产品选择,可视化和设计服务的系统和方法

    公开(公告)号:US20170004567A1

    公开(公告)日:2017-01-05

    申请号:US15198553

    申请日:2016-06-30

    CPC classification number: G06Q30/0643 G06Q30/0631 G06Q50/01

    Abstract: Systems, apparatuses, and methods for generating an on-line/eCommerce based garment viewing, selection, and sizing service that includes a virtual shopping experience capable of being initiated by activating an embedded uniform resource locator (URL) from an arbitrary web-based application or browser. The inventive system includes elements and processes that may be used to generate realistic images and behavior of a user's digital facsimile and associated clothing and/or accessories under different environmental viewing conditions (such as lighting, shading, etc.). These elements and processes may include mathematical/computational models of fabric appearance at both larger and smaller scales, fabric motion under conditions of wind or movement of a person wearing a garment, fabric reflectivity, garment seams, stylistic elements, etc. Models of a person generated by use of the inventive system may include consideration of one or more of a user's height, weight, age, skin tone, fitness level, hair, hair style, makeup, etc.

    Abstract translation: 用于生成基于在线/电子商务的服装查看,选择和尺寸服务的系统,装置和方法,其包括能够通过从任意的基于web的应用程序激活嵌入式统一资源定位符(URL)而启动的虚拟购物体验 或浏览器。 本发明的系统包括可用于在不同的环境观察条件(例如照明,阴影等)下产生用户的数字传真和相关衣服和/或附件的逼真图像和行为的元件和过程。 这些元素和过程可以包括在大尺寸和较小尺度的织物外观的数学/计算模型,织物在风的条件下运动或穿着衣服的人的运动,织物反射性,服装接缝,风格元素等。人的模型 通过使用本发明的系统产生的可以包括考虑用户的身高,体重,年龄,肤色,健身水平,头发,发型,化妆等中的一种或多种。

    Systems and methods for detecting anomalous system or network behavior

    公开(公告)号:US11381583B1

    公开(公告)日:2022-07-05

    申请号:US16178284

    申请日:2018-11-01

    Abstract: A system and associated methods for the detection of anomalous behavior in a system. In some embodiments, time-series data that is obtained from the system (such as log data) may be used as an input to a process that converts the data into greyscale values. The greyscale values are used to construct an “image” of the system operation that is used as an input to a convolutional neural network (CNN). The image is used to train the neural network so that the neural network is able to recognize when other input “images” constructed from time-series data are anomalous or otherwise indicative of a difference between the prior (and presumed normal or acceptable) and the current operation of the system.

Patent Agency Ranking