-
公开(公告)号：US20220108113A1
公开(公告)日：2022-04-07
申请号：US17061331
申请日：2020-10-01
摘要： A tunable signal sampling system includes a computing platform having a hardware processor and a memory storing a software code that when executed receives a communications signal, identifies data partitions included in the communications signal, performs, using a first predetermined metric, a first set of comparisons each comparing a different sequential pair of the data partitions with each other, and selects, based on the first set of comparisons, a subset of the data partitions as candidate sample partitions of the communications signal. The software code also determines multiple default sample partitions of the communications signal, performs, using a second predetermined metric, a second set of comparisons each comparing a different one of the default sample partitions with a respective one of the candidate sample partitions, and extracts, using a predetermined weighting factor applied to the results of the second set of comparisons, a sample of the communications signal.
-
公开(公告)号：US20230267754A1
公开(公告)日：2023-08-24
申请号：US17675953
申请日：2022-02-18
发明人： Miquel Angel Farre Guiu , Monica Alfaro Vendrell , Marc Junyet Martin , Francesc Josep Guitart Bravo , Albert Aparicio Isarn , Pablo Pernias , Steven S. Shapiro , Anthony M. Accardo
CPC分类号： G06V20/70 , G06V10/42 , G06V10/44 , G06V10/70 , G06V20/30 , G06V30/414 , G06V30/42 , G06V2201/131
摘要： A system includes a computing platform having processing hardware, and a systems memory storing a software code. The processing hardware is configured to execute the software code to receive content including an image having multiple image regions, determine boundaries of each of the image regions to identify multiple bounded image regions, identify, within each of the bounded image regions, one or more local features and one or more global features, and identify, within each of the hounded image regions, another one or more local features based on a comparison with corresponding local features identified in each of one or more other bounded image regions. The processing hardware is further configured to execute the software code to annotate each of the bounded image regions using its respective one or more local features, its other one or more local features, and its one or more global features, to provide annotated content.
-
公开(公告)号：US11741129B2
公开(公告)日：2023-08-29
申请号：US17396460
申请日：2021-08-06
发明人： Miquel Angel Farre Guiu , Monica Alfaro Vendrell , Marcel Porta Valles , Pablo Pernias , Marc Junyet Martin , Melina Ovanessian , Anthony M. Accardo , Mara Idai Lucien
IPC分类号： A61N1/00 , G06F16/28 , G06N20/00 , G06F16/2457
CPC分类号： G06F16/285 , G06F16/24573 , G06N20/00
摘要： According to one implementation, a system includes a computing platform having processing hardware, a system memory storing a software code; and a machine learning model based classifier. The processing hardware is configured to execute the software code to receive tagging quality assurance (QA) data including multiple terms applied as tags and corrections to those tags, to identify, using the tagging QA data, a first problematic term, and to classify, using the machine learning model based classifier, the first problematic term as one of confusing or flawed. The processing hardware is further configured to execute the software code to obtain, when the first problematic term is classified as confusing, a comparative sample for clarifying use of the first problematic term, and to obtain, when the first problematic term is classified as flawed, modification data for editing a predetermined annotation taxonomy including the first problematic term.
-
公开(公告)号：US20230068502A1
公开(公告)日：2023-03-02
申请号：US17460910
申请日：2021-08-30
发明人： Pablo Pernias , Monica Alfaro Vendrell , Francesc Josep Guitart Bravo , Marc Junyent Martin , Miquel Angel Farre Guiu
摘要： A system includes a computing platform having processing hardware, and a memory storing software code and a machine learning (ML) model-based feature classifier. When executed, the software code receives media content including a first media component corresponding to a first media mode and a second media component corresponding to a second media mode, encodes the first media component using a first encoder to generate multiple first embedding vectors, and encodes the second media component using a second encoder to generate multiple second embedding vectors. The software code further combines the first embedding vectors and the second embedding vectors to provide an input data structure for a neural network mixer, process, using the neural network mixer, the input data structure to provide feature data corresponding to a feature of the media content, and predict, using the ML model-based feature classifier and the feature data, a classification of the feature.
-
公开(公告)号：US12003831B2
公开(公告)日：2024-06-04
申请号：US17366675
申请日：2021-07-02
IPC分类号： H04N21/845 , G06N20/00 , H04N21/466 , H04N21/8352
CPC分类号： H04N21/8456 , G06N20/00 , H04N21/4662 , H04N21/8352
摘要： A content segmentation system includes a computing platform having processing hardware and a system memory storing a software code and a trained machine learning model. The processing hardware is configured to execute the software code to receive content, the content including multiple sections each having multiple content blocks in sequence, to select one of the sections for segmentation, and to identify, for each of the content blocks of the selected section, at least one respective representative unit of content. The software code is further executed to generate, using the at least one respective representative unit of content, a respective embedding vector for each of the content blocks of the selected section to provide a multiple embedding vectors, and to predict, using the trained machine learning model and the embedding vectors, subsections of the selected section, at least some of the subsections including more than one of the content blocks.
-
公开(公告)号：US20230267700A1
公开(公告)日：2023-08-24
申请号：US17675978
申请日：2022-02-18
发明人： Miquel Angel Farre Guiu , Monica Alfaro Vendrell , Pablo Pernias , Francesc Josep Guitart Bravo , Marc Junyent Martin , Albert Aparicio Isarn , Anthony M. Accardo , Steven S. Shapiro
CPC分类号： G06V10/25 , G06V10/462 , G06V20/70 , G06N20/20
摘要： A system includes a computing platform having processing hardware, and a memory storing software code. The processing hardware is configured to execute the software code to receive an image having a plurality of image regions, determine a boundary of each of the image regions to identify a plurality of bounded image regions, and identify, within each of the bounded image regions, one or more image sub-regions to identify a plurality of image sub-regions. The processing hardware is further configured to execute the software code to identify, within each of the bounded image regions, one or more first features, respectively, identify, within each of the image sub-regions, one or more second features, respectively, and provided an annotated image by annotating each of the bounded image regions using the respective first features and annotating each of the image sub-regions using the respective second features.
-
公开(公告)号：US20230007365A1
公开(公告)日：2023-01-05
申请号：US17366675
申请日：2021-07-02
IPC分类号： H04N21/845 , G06N20/00 , H04N21/8352 , H04N21/466
摘要： A content segmentation system includes a computing platform having processing hardware and a system memory storing a software code and a trained machine learning model. The processing hardware is configured to execute the software code to receive content, the content including multiple sections each having multiple content blocks in sequence, to select one of the sections for segmentation, and to identify, for each of the content blocks of the selected section, at least one respective representative unit of content. The software code is further executed to generate, using the at least one respective representative unit of content, a respective embedding vector for each of the content blocks of the selected section to provide a multiple embedding vectors, and to predict, using the trained machine learning model and the embedding vectors, subsections of the selected section, at least some of the subsections including more than one of the content blocks.
-
公开(公告)号：US11544828B2
公开(公告)日：2023-01-03
申请号：US16951580
申请日：2020-11-18
摘要： A method includes producing a filter mask based on a blur mask and a saliency mask and identifying locations of a plurality of bounding boxes of a plurality of objects of interest in a received image. The method also includes applying the filter mask to the received image and to the locations of the plurality of bounding boxes in the received image to remove at least one object of interest from consideration. The method further includes performing a comparison of a location of a bounding box of the plurality of bounding boxes of an object of interest remaining in consideration to a predetermined safe region of the received image and generating a validation result based on the comparison.
-
公开(公告)号：US20220343020A1
公开(公告)日：2022-10-27
申请号：US17703686
申请日：2022-03-24
摘要： A system includes a computing platform having processing hardware, and a system memory storing software code and a machine learning (ML) model. The processing hardware is configured to execute the software code to receive from a client, a request for a dataset, the request identifying a content type of the dataset, obtain the dataset having the content type, and select, based on the content type, an anonymization technique for the dataset, the anonymization technique selected so as to render at least one feature included in the dataset recognizable but unidentifiable. The processing hardware is further configured to execute the software code to anonymize, using the ML model and the selected anonymization technique, the at least one feature included in the dataset, and to output to the client, in response to the request, an anonymized dataset including the at least one anonymized feature.
-
公开(公告)号：US11386664B2
公开(公告)日：2022-07-12
申请号：US17061331
申请日：2020-10-01
摘要： A tunable signal sampling system includes a computing platform having a hardware processor and a memory storing a software code that when executed receives a communications signal, identifies data partitions included in the communications signal, performs, using a first predetermined metric, a first set of comparisons each comparing a different sequential pair of the data partitions with each other, and selects, based on the first set of comparisons, a subset of the data partitions as candidate sample partitions of the communications signal. The software code also determines multiple default sample partitions of the communications signal, performs, using a second predetermined metric, a second set of comparisons each comparing a different one of the default sample partitions with a respective one of the candidate sample partitions, and extracts, using a predetermined weighting factor applied to the results of the second set of comparisons, a sample of the communications signal.
-
-
-
-
-
-
-
-
-
搜索结果
17 条记录 (耗时 0.018 秒)
