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    WEAKLY SUPERVISED LEARNING FOR CLASSIFYING IMAGES
    51.
    发明申请
    WEAKLY SUPERVISED LEARNING FOR CLASSIFYING IMAGES 审中-公开

    公开(公告)号：US20200082224A1

    公开(公告)日：2020-03-12

    申请号：US16126748

    申请日：2018-09-10

    Applicant: SRI International

    Inventor： Karan Sikka ,  Ajay Divakaran ,  Parneet Kaur

    IPC: G06K9/62 ,  G06N3/08

    Abstract: Systems and methods for improving the accuracy of a computer system for object identification/classification through the use of weakly supervised learning are provided herein. In some embodiments, the method includes (a) receiving at least one set of curated data, wherein the curated data includes labeled images, (b) using the curated data to train a deep network model for identifying objects within images, wherein the trained deep network model has a first accuracy level for identifying objects, receiving a first target accuracy level for object identification of the deep network model, determining, automatically via the computer system, an amount of weakly labeled data needed to train the deep network model to achieve the first target accuracy level, and augmenting the deep network model using weakly supervised learning and the weakly labeled data to achieve the first target accuracy level for object identification by the deep network model.

    FOOD RECOGNITION USING VISUAL ANALYSIS AND SPEECH RECOGNITION
    56.
    发明申请
    FOOD RECOGNITION USING VISUAL ANALYSIS AND SPEECH RECOGNITION 审中-公开

    公开(公告)号：US20180075774A1

    公开(公告)日：2018-03-15

    申请号：US15818528

    申请日：2017-11-20

    Applicant: SRI International

    Inventor： Manika PURI ,  Zhiwei Zhu ,  Jeffrey Lubin ,  Tom Pschar ,  Ajay Divakaran ,  Harpreet Sawhney

    IPC: G09B19/00

    CPC classification number: G09B19/0092

    Abstract: A method and system for analyzing at least one food item on a food plate is disclosed. A plurality of images of the food plate is received by an image capturing device. A description of the at least one food item on the food plate is received by a recognition device. The description is at least one of a voice description and a text description. At least one processor extracts a list of food items from the description; classifies and segments the at least one food item from the list using color and texture features derived from the plurality of images; and estimates the volume of the classified and segmented at least one food item. The processor is also configured to estimate the caloric content of the at least one food item.

    Automated Food Recognition and Nutritional Estimation With a Personal Mobile Electronic Device
    58.
    发明申请
    Automated Food Recognition and Nutritional Estimation With a Personal Mobile Electronic Device 有权
    个人移动电子设备的自动食品识别和营养估计

    公开(公告)号：US20160063734A1

    公开(公告)日：2016-03-03

    申请号：US14567107

    申请日：2014-12-11

    Applicant: SRI International

    Inventor： Ajay Divakaran ,  Weiyu Zhang ,  Qian Yu ,  Harpreet S. Sawhney

    IPC: G06T7/40 ,  G06K9/46 ,  G06K9/62

    CPC classification number: G06K9/6202 ,  G06K9/4642 ,  G06K9/4671 ,  G06K9/6223 ,  G06K9/6269 ,  G06T2207/10024 ,  G06T2207/30128

    Abstract: A food recognition assistant system includes technologies to recognize foods and combinations of foods depicted in a digital picture of food. Some embodiments include technologies to estimate portion size and calories, and to estimate nutritional value of the foods. In some embodiments, data identifying recognized foods and related information are generated in an automated fashion without relying on human assistance to identify the foods. In some embodiments, the system includes technologies for achieving automatic food detection and recognition in a real-life setting with a cluttered background, without the images being taken in a controlled lab setting, and without requiring additional user input (such as user-defined bounding boxes). Some embodiments of the system include technologies for personalizing the food classification based on user-specific habits, location and/or other criteria.

    Abstract translation: 食品识别助理系统包括识别食物数字图片中描述的食物和食物组合的技术。 一些实施方案包括估计部分大小和热量的技术，以及估计食物的营养价值。 在一些实施例中，识别识别的食物和相关信息的数据以自动方式产生，而不依赖于人类帮助来识别食物。 在一些实施例中，该系统包括用于在具有混乱背景的现实生活设置中实现自动食物检测和识别的技术，而不将图像置于受控实验室设置中，并且不需要额外的用户输入（诸如用户定义的界限 盒）。 该系统的一些实施例包括基于用户特定习惯，位置和/或其他标准来个性化食品分类的技术。

    MULTI-MODAL MODELING OF TEMPORAL INTERACTION SEQUENCES
    59.
    发明申请
    MULTI-MODAL MODELING OF TEMPORAL INTERACTION SEQUENCES 审中-公开
    时间互动序列的多模式建模

    公开(公告)号：US20140212854A1

    公开(公告)日：2014-07-31

    申请号：US13755783

    申请日：2013-01-31

    Applicant: SRI INTERNATIONAL

    Inventor： Ajay Divakaran ,  Behjat Siddiquie ,  Saad Khan ,  Jeffrey Lubin ,  Harpreet S. Sawhney

    IPC: G09B25/00

    CPC classification number: G09B19/00

    Abstract: A multi-modal interaction modeling system can model a number of different aspects of a human interaction across one or more temporal interaction sequences. Some versions of the system can generate assessments of the nature or quality of the interaction or portions thereof, which can be used to, among other things, provide assistance to one or more of the participants in the interaction.

    Abstract translation: 多模式交互建模系统可以对一个或多个时间相互作用序列之间的人类交互的许多不同方面进行建模。 该系统的一些版本可以产生相互作用或其部分的性质或质量的评估，其可以用于向交互中的一个或多个参与者提供帮助。

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