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公开(公告)号：US12111850B2
公开(公告)日：2024-10-08
申请号：US17715649
申请日：2022-04-07
发明人： Tyler Folkman , Rey Furner
CPC分类号： G06F16/285 , G06F16/2246 , G06F16/288 , G06N20/00 , G06F17/11
摘要： Systems and methods for determining whether two tree persons in a genealogical database correspond to the same real-life individual. Embodiments include obtaining, from a tree database, a first tree person from a first genealogical tree and a second tree person from a second genealogical tree. Embodiments also include identifying a plurality of familial categories. Embodiments further include, for each familial category of the plurality of familial categories, extracting a first quantity of features for each of the tree persons in the familial category, generating a first similarity score for each possible pairing of tree persons, identifying a representative pairing based on a maximum first similarity score, and extracting a second quantity of features for each of the tree persons in the representative pairing. Embodiments may also include generating a second similarity score based on the second quantity of features.
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公开(公告)号：US20230325373A1
公开(公告)日：2023-10-12
申请号：US18121997
申请日：2023-03-15
IPC分类号： G06F40/295 , G06V30/32 , G06V30/413 , G06F16/22 , G06V30/416
CPC分类号： G06F16/2246 , G06F40/295 , G06V30/333 , G06V30/413 , G06V30/416
摘要： Systems and methods for importing documents are described. An input image is received and preprocessed. OCR and/or page segmentation and chapter detection are performed. Special-case processing is performed for lists, tables, free text, and other categories. Anaphora analysis, stemming, lemmatization, and relationship detection are performed. A genealogical tree is generated, augmented, or merged based on the extracted entities and relationships.
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公开(公告)号：US20230161796A1
公开(公告)日：2023-05-25
申请号：US18057904
申请日：2022-11-22
IPC分类号： G06F16/28 , G06F16/22 , G06F3/0482
CPC分类号： G06F16/287 , G06F16/2246 , G06F3/0482
摘要： A family tree interface may include a default number of family members in addition to a target node which are expandable upon selection by a user. The default tree interface is expandable by a user vertically to include more generations and laterally. The tree interface includes labels showing a relationship of a tree node to the target node. In some embodiments, one or more family members that have not been rendered may be cached to speed up the visual rendering process. A graphical user interface, in a viewing session, may display an initial view of the family tree associated with the target individual. Upon receipt of an expand request, the viewing session may add the one or more additional family members to generate an expanded view of the family tree. The expanded view may partially adjust the initial view without refreshing the viewing session.
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公开(公告)号：US20230083000A1
公开(公告)日：2023-03-16
申请号：US17895818
申请日：2022-08-25
摘要： OCR-text correction system and method embodiments are described. The OCR-text correction embodiments comprise or cooperate with a transformer-based sequence-to-sequence language model. The model is pretrained to denoise corrupted text and is fine-tuned using OCR-correction-specific examples. Text obtained at least in part through OCR is applied to the fine-tuned pretrained transformer model to detect at least one error in a subset of the text. Responsive to detecting the at least one error, the fine-tuned pretrained transformer model outputs an updated subset of the text to correct the at least one error.
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公开(公告)号：US20220253604A1
公开(公告)日：2022-08-11
申请号：US17667320
申请日：2022-02-08
发明人： Yingrui Yang , Yen-Yun Yu
IPC分类号： G06F40/289 , G06F40/284 , G06F40/30
摘要： Described herein are systems, methods, and other techniques for extracting one or more keyphrases from an input text. The input text may include a plurality of words. A plurality of token-level attention matrices may be generated using a transformer-based machine learning model. The plurality of token-level attention matrices may be converted into a plurality of word-level attention matrices. A set of candidate phrases may be identified from the plurality of words based on the plurality of word-level attention matrices. The one or more keyphrases may be selected from the set of candidate phrases.
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公开(公告)号：US20220189188A1
公开(公告)日：2022-06-16
申请号：US17643545
申请日：2021-12-09
IPC分类号： G06V30/226 , G06K9/62 , G06N3/04
摘要： A simplified handwriting recognition approach includes a first network comprising convolutional neural network comprising one or more convolutional layers and one or more max-pooling layers. The first network receives an input image of handwriting and outputs an embedding based thereon. A second network comprises a network of cascaded convolutional layers including one or more subnetworks configured to receive an embedding of a handwriting image and output one or more character predictions. The subnetworks are configured to downsample and flatten the embedding to a feature map and then a vector before passing the vector to a dense neural network for character prediction. Certain subnetworks are configured to concatenate an input embedding with an upsampled version of the feature map.
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公开(公告)号：US11321361B2
公开(公告)日：2022-05-03
申请号：US16758757
申请日：2018-10-19
发明人： Tyler Folkman , Rey Furner
摘要： Systems and methods for determining whether two tree persons in a genealogical database correspond to the same real-life individual. Embodiments include obtaining, from a tree database, a first tree person from a first genealogical tree and a second tree person from a second genealogical tree. Embodiments also include identifying a plurality of familial categories. Embodiments further include, for each familial category of the plurality of familial categories, extracting a first quantity of features for each of the tree persons in the familial category, generating a first similarity score for each possible pairing of tree persons, identifying a representative pairing based on a maximum first similarity score, and extracting a second quantity of features for each of the tree persons in the representative pairing. Embodiments may also include generating a second similarity score based on the second quantity of features.
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公开(公告)号：US20210390704A1
公开(公告)日：2021-12-16
申请号：US17343626
申请日：2021-06-09
摘要： Systems and methods for identifying and segmenting objects from images include a preprocessing module configured to adjust a size of a source image; a region-proposal module configured to propose one or more regions of interest in the size-adjusted source image; and a prediction module configured to predict a classification, bounding box coordinates, and mask. Such systems and methods may utilize end-to-end training of the modules using adversarial loss, facilitating the use of a small training set, and can be configured to process historical documents, such as large images comprising text. The preprocessing module within said systems and methods can utilize a conventional image scaler in tandem with a custom image scaler to provide a resized image suitable for GPU processing, and the region-proposal module can utilize a region-proposal network from a single-stage detection model in tandem with a two-stage detection model paradigm to capture substantially all particles in an image.
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公开(公告)号：US20210365803A1
公开(公告)日：2021-11-25
申请号：US17392695
申请日：2021-08-03
发明人： Atanu Roy , Jianlong Qi , Peng Jiang , Aaron Ling , Rey Furner , Lei Wu , Eugene Greenwood , Ian Stiles
摘要： Systems and methods for determining whether two tree persons in a genealogical database correspond to the same real-life individual. Embodiments include identifying two tree persons in a genealogical database and extracting a plurality of features from both tree persons to generate two vectors. Embodiments also include calculating a plurality of metrics between the two vectors to generate a metric function. Embodiments further include generating feature weights using a recursive process based on training data input by external users, and generating a score by calculating a weighted sum of the metric function being weighted by the feature weights. The generated score may then be compared to a threshold value.
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公开(公告)号：US20210174083A1
公开(公告)日：2021-06-10
申请号：US17178822
申请日：2021-02-18
摘要： Embodiments described herein relate generally to a methodology of efficient object classification within a visual medium. The methodology utilizes a first neural network to perform an attention based object localization within a visual medium to generate a visual mask. The visual mask is applied to the visual medium to generate a masked visual medium. The masked visual medium may be then fed into a second neural network to detect and classify objects within the visual medium.
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