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    Methods and systems for hierarchical dynamic cataloging
    1.
    发明授权
    Methods and systems for hierarchical dynamic cataloging 有权

    公开(公告)号：US11586596B2

    公开(公告)日：2023-02-21

    申请号：US16596986

    申请日：2019-10-09

    Applicant: Tata Consultancy Services Limited

    Inventor： Satanik Panda ,  Dibyendu Biswas ,  Hemanta Dutta ,  Tanushyam Chattopadhyay ,  Prateep Misra

    IPC: G06F16/00 ,  G06F16/21 ,  G06F16/28 ,  G06Q10/105 ,  G06N20/00 ,  G06F16/23

    Abstract: Data cataloging has become a necessity for empowering organizations with analytical ability. Conventional cataloging systems may fail to provide proper visualization of data to the different stakeholders of an organization. The present disclosure provides a hierarchical dynamic cataloging system so that visualization of data at different levels would be possible for different stake holders. In the present disclosure, a hierarchical structure of algorithms and multiple stake holders along with relevant metadata is generated. Further, a catalog is generated by performing a mapping across components comprised in the hierarchical structure and identifying relationship across the components based on mapping. The catalog gets dynamically updated and provides a dynamic view of the algorithms and associated metadata to the multiple stakeholders of an organization. Further, the disclosure supports reuse of already developed algorithms across multiple applications and domains resulting in optimization of resources and time.

    Systems and methods for obtaining optimal mother wavelets for facilitating machine learning tasks
    2.
    发明授权
    Systems and methods for obtaining optimal mother wavelets for facilitating machine learning tasks 有权

    公开(公告)号：US11475341B2

    公开(公告)日：2022-10-18

    申请号：US16179771

    申请日：2018-11-02

    Applicant: Tata Consultancy Services Limited

    Inventor： Ishan Sahu ,  Snehasis Banerjee ,  Tanushyam Chattopadhyay ,  Arpan Pal ,  Utpal Garain

    IPC: G06N7/00 ,  G06F17/14 ,  G06N20/00 ,  G06F17/18 ,  G06K9/62

    Abstract: Systems and methods for obtaining optimal mother wavelets for facilitating machine learning tasks. The traditional systems and methods provide for selecting a mother wavelet and signal classification using some traditional techniques and methods but none them provide for selecting an optimal mother wavelet to facilitate machine learning tasks. Embodiments of the present disclosure provide for obtaining an optimal mother wavelet to facilitate machine learning tasks by computing values of energy and entropy based upon labelled datasets and a probable set of mother wavelets, computing values of centroids and standard deviations based upon the values of energy and entropy, computing a set of distance values and normalizing the set of distance values and obtaining the optimal mother wavelet based upon the set of distance values for performing a wavelet transform and further facilitating machine learning tasks by classifying or regressing, a new set of signal classes, corresponding to a new set of signals.

    Signal analysis systems and methods for features extraction and interpretation thereof
    3.
    发明授权
    Signal analysis systems and methods for features extraction and interpretation thereof 有权

    公开(公告)号：US10664698B2

    公开(公告)日：2020-05-26

    申请号：US15900987

    申请日：2018-02-21

    Applicant: Tata Consultancy Services Limited

    Inventor： Snehasis Banerjee ,  Tanushyam Chattopadhyay ,  Ayan Mukherjee

    IPC: G06K9/00 ,  G06F16/2455 ,  G06K9/62 ,  G06N3/10

    Abstract: Development of sensor data based descriptive and prescriptive system involves machine learning tasks like classification and regression. Any such system development requires the involvement of different stake-holders for obtaining features. Such features typically obtained are not interpretable for 1-D sensor signals. Embodiments of the present disclosure provide systems and methods that perform signal analysis for features extraction and interpretation thereof wherein input is raw signal data where origin of a feature is traced to signal data, and mapped to domain/application knowledge. Feature(s) are extracted using deep learning network(s) and machine learning (ML) model(s) are implemented for sensor data analysis to perform causality analysis for prognostics. Layer(s) (say last layer) of Deep Network(s) contains the automatically derived features that can be used for ML tasks. Parameter(s) tuning is performed based on the set of features that were recommended by the system to determined performance of systems (or applications) under consideration.

    Static posture based person identification
    4.
    发明授权
    Static posture based person identification 有权

    公开(公告)号：US10198694B2

    公开(公告)日：2019-02-05

    申请号：US14588595

    申请日：2015-01-02

    Applicant: Tata Consultancy Services Limited

    Inventor： Kingshuk Chakravarty ,  Ramu Reddy Vempada ,  Tanushyam Chattopadhyay ,  Aniruddha Sinha ,  Arpan Pal

    IPC: G06F15/18 ,  G06N5/04 ,  G06K9/00 ,  G01J5/00 ,  G06N99/00 ,  G06F21/32

    Abstract: A system and method for identifying an unknown person based on a static posture of the unknown person is described. The method includes receiving data of N skeleton joints of the unknown person from a skeleton recording device. The method further includes identifying the static posture of the unknown person. The method includes dividing a skeleton structure of the unknown person in a plurality of body parts based on joint types of the skeleton structure. In addition, the method includes extracting feature vectors for each of the joint type from each of the plurality of body parts. The method further includes identifying the unknown person based on comparison of the feature vectors for the unknown person with one of a constrained feature dataset and an unconstrained feature dataset for a plurality of known persons.

    ANNOTATION OF TIME SERIES DATA AND VALIDATION FOR GENERATING MACHINE LEARNING MODELS
    5.
    发明申请
    ANNOTATION OF TIME SERIES DATA AND VALIDATION FOR GENERATING MACHINE LEARNING MODELS 有权

    公开(公告)号：US20220092474A1

    公开(公告)日：2022-03-24

    申请号：US17366810

    申请日：2021-07-02

    Applicant: Tata Consultancy Services Limited

    Inventor： Tanushyam Chattopadhyay ,  Arijit Ukil ,  Avijit Sur ,  Prateep Misra ,  Arpan Pal ,  Soma Bandyopadhyay

    IPC: G06N20/00 ,  G06F16/28

    Abstract: Conventionally, applying analytics on dataset is the scarcity of labelled data. With increase of data there is cost fact effecting nature of servicing required for data (e.g., cost in terms of resource and time and effort is high for data annotation). Though data is analysed, it may be prone to error. Present disclosure provides systems/methods for reducing volume of data to be annotated for time series data thereby reducing time and effort of resources, thus resulting in effective utilization of system's resources (e.g., memory, processor, etc.). More specifically, the method of the present disclosure adaptively modifies the volume of the data to be annotated based on the performance of the unsupervised learning method applied in the system. Moreover, in the absence of an annotation mechanism for clusters of time series data, meta data associated with the time series data is utilized for annotation and validation of dataset.

    System and Method for Detection and Segmentation of Touching Characters for OCR
    9.
    发明申请
    System and Method for Detection and Segmentation of Touching Characters for OCR 有权
    OCR触摸字符的检测和分割系统及方法

    公开(公告)号：US20150086113A1

    公开(公告)日：2015-03-26

    申请号：US14387094

    申请日：2013-03-20

    Applicant: Tata Consultancy Services Limited ,  Indian Statistical Institute

    Inventor： Tanushyam Chattopadhyay ,  Arpan Pal ,  Aniruddha Sinha ,  Utpal Garain

    IPC: G06K9/34

    CPC classification number: G06K9/344 ,  G06K9/342 ,  G06K9/348

    Abstract: The present disclosure relates to a system and a method for detection of touching characters in a media, characterized by segmentation of adjoining character spaces. In the very first step, an aspect ratio is calculated for each connected component. A candidate touching position of each character is determined by calculating a threshold aspect ratio for each character. Further, a candidate cut column is determined based on a relation between column pixel densities and corresponding length thereof the column in order to segment the touching characters at the candidate cut column.

    Abstract translation: 本公开涉及一种用于检测媒体中的触摸人物的系统和方法，其特征在于相邻字符空间的分割。 在第一步中，为每个连接的组件计算宽高比。 通过计算每个字符的阈值长宽比来确定每个字符的候选者触摸位置。 此外，基于列像素密度与列的相应长度之间的关系来确定候选剪切列，以便在候选剪切列处分割触摸字符。

    METHOD AND SYSTEM FOR AUTOMATIC SELECTION OF ONE OR MORE IMAGE PROCESSING ALGORITHM
    10.
    发明申请
    METHOD AND SYSTEM FOR AUTOMATIC SELECTION OF ONE OR MORE IMAGE PROCESSING ALGORITHM 有权
    用于自动选择一个或多个图像处理算法的方法和系统

    公开(公告)号：US20140348420A1

    公开(公告)日：2014-11-27

    申请号：US14286303

    申请日：2014-05-23

    Applicant: Tata Consultancy Services Limited

    Inventor： Tanushyam Chattopadhyay ,  Ramu Vempada Reddy ,  Utpal Garain

    IPC: G06K9/66 ,  G06K9/48 ,  G06K9/34

    CPC classification number: G06K9/66 ,  G06K9/34 ,  G06K9/38 ,  G06K9/4652 ,  G06K9/481 ,  G06K2209/01

    Abstract: Disclosed is a method and system for automatic algorithm selection for image processing. The invention discloses the method and system for automatically selecting the correct algorithm(s) for a varying requirement of the image for processing. The selection of algorithm is completely automatic and guided by a plurality of machine learning approaches. The system here is configured to pre-process plurality of images for creating a training data. Next, the test image is extracted, pre-processed and matched for assessing the best possible match of algorithm for processing.

    Abstract translation: 公开了用于图像处理的自动算法选择的方法和系统。 本发明公开了用于自动选择用于处理图像的变化需求的正确算法的方法和系统。 算法的选择是完全自动的，并由多种机器学习方法引导。 这里的系统被配置为预处理用于创建训练数据的多个图像。 接下来，提取测试图像，预处理和匹配，以评估用于处理的算法的最佳匹配。

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