公开(公告)号：US11335062B2

公开(公告)日：2022-05-17

申请号：US16994270

申请日：2020-08-14

Applicant: Accenture Global Solutions Limited

Inventor： Payal Argarwal ,  Vaibhav Kumar Daga ,  Parag Rane ,  Prasanna Srinivasa Rao ,  Ratan Yashwant Panjwani

IPC: G06T17/20 ,  G10L15/26 ,  A41D1/00 ,  G06N3/04 ,  G06F40/35 ,  G06N20/00

Abstract: Aspects of the present disclosure provide systems, methods, and computer-readable storage media facilitating automated apparel design using deep learning techniques. For example, user instructions may be received as text data (or converted to text data from audio data representing user speech), and natural language processing (NLP) may be performed on the text data to interpret the user instructions. An apparel design may be generated in real-time/substantially real-time based on the user instructions. For example, the interpreted user instructions may be provided as input to at least one machine learning (ML) model that is configured to determine one or more visual apparel elements based on the user instructions and to generate the apparel design based on the visual apparel elements. One or more operations may be initiated based on the apparel design.

公开(公告)号：US11416867B2

公开(公告)日：2022-08-16

申请号：US16906044

申请日：2020-06-19

Applicant: Accenture Global Solutions Limited

Inventor： Maria Lopes ,  Gopali Raval Contractor ,  Subhashini Lakshminarayanan ,  Prasanna S R ,  Parag Rane ,  Arati Deo ,  Azimullah Shahzad ,  Vallinath Sriramula

IPC: G06Q40/00 ,  G06Q20/40 ,  G06Q20/42 ,  G06N3/04

Abstract: A device may receive transaction data associated with transactions. The transaction data may be associated with transaction entries that are associated with the transactions. The device may process, using a matching model, the transaction entries to classify the transaction entries into a set of matched transaction entries and a set of unmatched transaction entries. The device may update a transaction grouping model based on the set of matched transaction entries to create an updated transaction grouping model. The device may determine, using the updated transaction grouping model, that a subset of the set of unmatched transaction entries are associated with a same transaction. The device may classify the subset of the set of unmatched transaction entries as grouped transaction entries. The device may provide an indication that the grouped transaction entries and the set of matched transaction entries are reconciled transactions.