公开(公告)号：US20200175304A1

公开(公告)日：2020-06-04

申请号：US16353570

申请日：2019-03-14

Applicant: Tata Consultancy Services Limited

Inventor： Lovekesh VIG ,  Gautam SHROFF ,  Arindam CHOWDHURY ,  Rohit RAHUL ,  Gunjan SEHGAL ,  Vishwanath DORESWAMY ,  Monika SHARMA ,  Ashwin SRINIVASAN

IPC: G06K9/46 ,  G06F17/27 ,  G06T5/00 ,  G06K9/00 ,  G06K9/62 ,  G06F16/2452 ,  G06F16/2455 ,  G06F16/28 ,  G06N3/08

Abstract: Various methods are using SQL based data extraction for extracting relevant information from images. These are rule based methods of generating SQL-Query from NL, if any new English sentences are to be handled then manual intervention is required. Further becomes difficult for non-technical user. A system and method for extracting relevant from the images using a conversational interface and database querying have been provided. The system eliminates noisy effects, identifying the type of documents and detect various entities for diagrams. Further a schema is designed which allows an easy to understand abstraction of the entities detected by the deep vision models and the relationships between them. Relevant information and fields can then be extracted from the document by writing SQL queries on top of the relationship tables. A natural language based interface is added so that a non-technical user, specifying the queries in natural language, can fetch the information effortlessly.

公开(公告)号：US20200175372A1

公开(公告)日：2020-06-04

申请号：US16381316

申请日：2019-04-11

Applicant: Tata Consultancy Services Limited

Inventor： Monika SHARMA ,  Rohit RAHUL ,  Lovekesh VIG ,  Shubham PALIWAL

IPC: G06N3/08 ,  G06N3/04 ,  G06F16/901 ,  G06F16/9035

Abstract: Systems and methods for automating information extraction from piping and instrumentation diagrams is provided. Traditional systems and methods do not provide for end-to-end and automated data extraction from the piping and instrumentation diagrams. The method disclosed provides for automatic generation of end-to-end information from piping and instrumentation diagrams by detecting, via one or more hardware processors, a plurality of components from one or more piping and instrumentation diagrams by implementing one or more image processing and deep learning techniques; associating, via an association module, each of the detected plurality of components by implementing a Euclidean Distance technique; and generating, based upon each of the associated plurality of components, a plurality of tree-shaped data structures by implementing a structuring technique, wherein each of the plurality of tree-shaped data structures capture a process flow of pipeline schematics corresponding to the one or more piping and instrumentation diagrams.

公开(公告)号：US20200167557A1

公开(公告)日：2020-05-28

申请号：US16285107

申请日：2019-02-25

Applicant: Tata Consultancy Services Limited

Inventor： Rohit RAHUL ,  Arindam CHOWDHURY ,  Lovekesh VIG ,  . ANIMESH ,  Samarth MITTAL

IPC: G06K9/00 ,  G06K9/20 ,  G06N3/04 ,  G06K9/62 ,  G06T7/136 ,  G06F17/15

Abstract: This disclosure relates to digitization of industrial inspection sheets. Digital scanning of paper based inspection sheets is a common process in factory settings. The paper based scans have data pertaining to millions of faults detected over several decades of inspection. The technical challenge ranges from image preprocessing and layout analysis to word and graphic item recognition. This disclosure provides a visual pipeline that works in the presence of both static and dynamic background in the scans, variability in machine template diagrams, unstructured shape of graphical objects to be identified and variability in the strokes of handwritten text. The pipeline incorporates a capsule and spatial transformer network based classifier for accurate text reading and a customized Connectionist Text Proposal Network (CTPN) for text detection in addition to hybrid techniques for arrow detection and dialogue cloud removal.