Patents by Inventor Seyed Hamed Yaghoubi SHAHIR
Seyed Hamed Yaghoubi SHAHIR has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20240046333Abstract: Disclosed methods and system describe a server that uses AI modeling to predict negative cash flow at a user level. The server periodically retrieves data associated with the user, the data comprising monetary attributes associated with one or more accounts of the user; executes a deep neural network model trained based upon historical data associated with at least a subset of the users configured to predict a negative cash flow in one or more accounts of the user, a depth of the negative cash flow, and a duration of the negative cash flow; transmits, to a second server, the predicted values, whereby when the second server determines that a likelihood of account needs satisfies a threshold, the second server establishes an electronic communication session with an electronic device of the user; trains the deep neural network when the second server establishes the electronic communication session.Type: ApplicationFiled: October 17, 2023Publication date: February 8, 2024Applicant: BANK OF MONTREALInventors: Seyed Masoud NOSRATI, Evgene VAHLIS, Seyed Hamed Yaghoubi SHAHIR, Bo ZHAO, Nicole LANGBALLE, Peter POON
-
Publication number: 20230342610Abstract: Disclosed are methods and systems for using artificial intelligence (AI) for image recognition by using predefined coordinates to extract a portion of a received image, the extracted portion comprising a word to be identified having at least a first letter and a second letter; executing an image recognition protocol to identify the first letter; when the server is unable to identify the second letter, the server executes an AI model having a nodal data structure to identify the second letter based upon the identified first letter, the nodal data structure comprising a set of nodes where each node represents a letter, each node connected to at least one other node, wherein connection of a first node to a second node corresponds to a probability that a letter corresponding to the second node is used in a word subsequent to a letter corresponding to the first node.Type: ApplicationFiled: June 30, 2023Publication date: October 26, 2023Applicant: Bank of MontrealInventors: Bo WU, Ching Leong WAN, Yuefei ZHU, Bo WAN, Seyed Hamed Yaghoubi SHAHIR
-
Patent number: 11798059Abstract: Disclosed methods and system describe a server that uses AI modeling to predict negative cash flow at a user level. The server periodically retrieves data associated with the user, the data comprising monetary attributes associated with one or more accounts of the user; executes a deep neural network model trained based upon historical data associated with at least a subset of the users configured to predict a negative cash flow in one or more accounts of the user, a depth of the negative cash flow, and a duration of the negative cash flow; transmits, to a second server, the predicted values, whereby when the second server determines that a likelihood of account needs satisfies a threshold, the second server establishes an electronic communication session with an electronic device of the user; trains the deep neural network when the second server establishes the electronic communication session.Type: GrantFiled: April 8, 2021Date of Patent: October 24, 2023Assignee: BANK OF MONTREALInventors: Seyed Masoud Nosrati, Evgene Vahlis, Seyed Hamed Yaghoubi Shahir, Bo Zhao, Nicole Langballe, Peter Poon
-
Patent number: 11769054Abstract: Disclosed are methods and systems for using artificial intelligence (AI) for image recognition by using predefined coordinates to extract a portion of a received image, the extracted portion comprising a word to be identified having at least a first letter and a second letter; executing an image recognition protocol to identify the first letter; when the server is unable to identify the second letter, the server executes an AI model having a nodal data structure to identify the second letter based upon the identified first letter, the nodal data structure comprising a set of nodes where each node represents a letter, each node connected to at least one other node, wherein connection of a first node to a second node corresponds to a probability that a letter corresponding to the second node is used in a word subsequent to a letter corresponding to the first node.Type: GrantFiled: January 14, 2022Date of Patent: September 26, 2023Assignee: BANK OF MONTREALInventors: Bo Wu, Ching Leong Wan, Yuefei Zhu, Bo Wan, Seyed Hamed Yaghoubi Shahir
-
Publication number: 20220139095Abstract: Disclosed are methods and systems for using artificial intelligence (AI) for image recognition by using predefined coordinates to extract a portion of a received image, the extracted portion comprising a word to be identified having at least a first letter and a second letter; executing an image recognition protocol to identify the first letter; when the server is unable to identify the second letter, the server executes an AI model having a nodal data structure to identify the second letter based upon the identified first letter, the nodal data structure comprising a set of nodes where each node represents a letter, each node connected to at least one other node, wherein connection of a first node to a second node corresponds to a probability that a letter corresponding to the second node is used in a word subsequent to a letter corresponding to the first node.Type: ApplicationFiled: January 14, 2022Publication date: May 5, 2022Applicant: Bank of MontrealInventors: Bo WU, Ching Leong WAN, Yuefei ZHU, Bo WAN, Seyed Hamed Yaghoubi SHAHIR
-
Patent number: 11227176Abstract: Disclosed are methods and systems for using artificial intelligence (AI) for image recognition by using predefined coordinates to extract a portion of a received image, the extracted portion comprising a word to be identified having at least a first letter and a second letter; executing an image recognition protocol to identify the first letter; when the server is unable to identify the second letter, the server executes an AI model having a nodal data structure to identify the second letter based upon the identified first letter, the nodal data structure comprising a set of nodes where each node represents a letter, each node connected to at least one other node, wherein connection of a first node to a second node corresponds to a probability that a letter corresponding to the second node is used in a word subsequent to a letter corresponding to the first node.Type: GrantFiled: May 12, 2020Date of Patent: January 18, 2022Assignee: BANK OF MONTREALInventors: Bo Wu, Ching Leong Wan, Yuefei Zhu, Bo Wan, Seyed Hamed Yaghoubi Shahir
-
Publication number: 20210326960Abstract: Disclosed methods and system describe a server that uses AI modeling to predict negative cash flow at a user level. The server periodically retrieves data associated with the user, the data comprising monetary attributes associated with one or more accounts of the user; executes a deep neural network model trained based upon historical data associated with at least a subset of the users configured to predict a negative cash flow in one or more accounts of the user, a depth of the negative cash flow, and a duration of the negative cash flow; transmits, to a second server, the predicted values, whereby when the second server determines that a likelihood of account needs satisfies a threshold, the second server establishes an electronic communication session with an electronic device of the user; trains the deep neural network when the second server establishes the electronic communication session.Type: ApplicationFiled: April 8, 2021Publication date: October 21, 2021Inventors: Seyed Masoud NOSRATI, Evgene VAHLIS, Seyed Hamed Yaghoubi SHAHIR, Bo ZHAO, Nicole LANGBALLE, Peter POON
-
Publication number: 20200364485Abstract: Disclosed are methods and systems for using artificial intelligence (AI) for image recognition by using predefined coordinates to extract a portion of a received image, the extracted portion comprising a word to be identified having at least a first letter and a second letter; executing an image recognition protocol to identify the first letter; when the server is unable to identify the second letter, the server executes an AI model having a nodal data structure to identify the second letter based upon the identified first letter, the nodal data structure comprising a set of nodes where each node represents a letter, each node connected to at least one other node, wherein connection of a first node to a second node corresponds to a probability that a letter corresponding to the second node is used in a word subsequent to a letter corresponding to the first node.Type: ApplicationFiled: May 12, 2020Publication date: November 19, 2020Inventors: Bo WU, Ching Leong WAN, Yuefei ZHU, Bo WAN, Seyed Hamed Yaghoubi SHAHIR