公开(公告)号：US20210166074A1

公开(公告)日：2021-06-03

申请号：US17169825

申请日：2021-02-08

申请人： Ernst & Young U.S. LLP

发明人： Dan G. TECUCI ,  Ravi Kiran Reddy PALLA ,  Hamid Reza Motahari NEZHAD ,  Vincent POON ,  Nigel Paul DUFFY ,  Joseph NIPKO

IPC分类号： G06K9/62 ,  G06F3/0482 ,  G06K9/00 ,  G06N3/02 ,  G06N20/20

摘要： An object-extraction method includes generating multiple partition objects based on an electronic document, and receiving a first user selection of a data element via a user interface of a compute device. In response to the first user selection, and using a machine learning model, a first subset of partition objects from the multiple partition objects is detected and displayed via the user interface. A user interaction, via the user interface, with one of the partition objects is detected, and in response, a weight of the machine learning model is modified, to produce a modified machine learning model. A second user selection of the data element is received via the user interface, and in response and using the modified machine learning model, a second subset of partition objects from the multiple partition objects is detected and displayed via the user interface, the second subset different from the first subset.

公开(公告)号：US20240232626A1

公开(公告)日：2024-07-11

申请号：US18583459

申请日：2024-02-21

申请人： Ernst & Young U.S. LLP

发明人： Vincent POON ,  Nigel Paul DUFFY ,  Ravi Kiran Reddy PALLA

IPC分类号： G06N3/08 ,  G06N3/045

CPC分类号： G06N3/08 ,  G06N3/045

摘要： A multi-label ranking method includes receiving, at a processor and from a first set of artificial neural networks (ANNs), multiple signals representing a first set of ANN output pairs for a first label. A signal representing a second set of ANN output pairs for a second label different from the first label is received at the processor from a second set of ANNs different from the first set of ANNs, substantially concurrently with the first set of ANN output pairs. A first activation function is solved based on the first set of ANN output pairs, and a second activation function is solved based on the second set of ANN output pairs. Loss values are calculated based on the solved activations, and a mask is generated based on at least one ground truth label. A signal, including a representation of the mask, is sent from the processor to each of the sets of ANNs.

公开(公告)号：US20200327407A1

公开(公告)日：2020-10-15

申请号：US16381505

申请日：2019-04-11

申请人： Ernst & Young U.S. LLP

发明人： Vincent POON ,  Nigel Paul DUFFY ,  Ravi Kiran Reddy PALLA

IPC分类号： G06N3/08 ,  G06N3/04

摘要： A multi-label ranking method includes receiving, at a processor and from a first set of artificial neural networks (ANNs), multiple signals representing a first set of ANN output pairs for a first label. A signal representing a second set of ANN output pairs for a second label different from the first label is received at the processor from a second set of ANNs different from the first set of ANNs, substantially concurrently with the first set of ANN output pairs. A first activation function is solved based on the first set of ANN output pairs, and a second activation function is solved based on the second set of ANN output pairs. Loss values are calculated based on the solved activations, and a mask is generated based on at least one ground truth label. A signal, including a representation of the mask, is sent from the processor to each of the sets of ANNs.

公开(公告)号：US20200327373A1

公开(公告)日：2020-10-15

申请号：US16790945

申请日：2020-02-14

申请人： Ernst & Young U.S. LLP

发明人： Dan G. TECUCI ,  Ravi Kiran Reddy PALLA ,  Hamid Reza Motahari NEZHAD ,  Vincent POON ,  Nigel Paul DUFFY ,  Joseph NIPKO

IPC分类号： G06K9/62 ,  G06K9/00 ,  G06N3/02 ,  G06N20/20 ,  G06F3/0482

摘要： An object-extraction method includes generating multiple partition objects based on an electronic document, and receiving a first user selection of a data element via a user interface of a compute device. In response to the first user selection, and using a machine learning model, a first subset of partition objects from the multiple partition objects is detected and displayed via the user interface. A user interaction, via the user interface, with one of the partition objects is detected, and in response, a weight of the machine learning model is modified, to produce a modified machine learning model. A second user selection of the data element is received via the user interface, and in response and using the modified machine learning model, a second subset of partition objects from the multiple partition objects is detected and displayed via the user interface, the second subset different from the first subset.