公开(公告)号：US11971963B2

公开(公告)日：2024-04-30

申请号：US16407033

申请日：2019-05-08

申请人： Quantum-Si Incorporated

发明人： Umut Eser ,  Michael Meyer

IPC分类号： G06F18/25 ,  G06F18/2135 ,  G06F18/214 ,  G06F18/22

CPC分类号： G06F18/256 ,  G06F18/21355 ,  G06F18/214 ,  G06F18/22

摘要： Methods and apparatus for predicting an association between input data in a first modality and data in a second modality using a statistical model trained to represent interactions between data having a plurality of modalities including the first modality and the second modality, the statistical model comprising a plurality of encoders and decoders, each of which is trained to process data for one of the plurality of modalities, and a joint-modality representation coupling the plurality of encoders and decoders. The method comprises selecting, based on the first modality and the second modality, an encoder/decoder pair or a pair of encoders, from among the plurality of encoders and decoders, and processing the input data with the joint-modality representation and the selected encoder/decoder pair or pair of encoders to predict the association between the input data and the data in the second modality.

公开(公告)号：US20230259588A1

公开(公告)日：2023-08-17

申请号：US18154603

申请日：2023-01-13

申请人： Illumina, Inc.

发明人： Eric Jon OJARD ,  Abde Ali Hunaid KAGALWALLA ,  Rami MEHIO ,  Nitin UDPA ,  Gavin Derek PARNABY ,  John S. VIECELI

IPC分类号： G06F18/2411 ,  G06T7/187 ,  G06V10/50 ,  G06F18/2135

CPC分类号： G06F18/2411 ,  G06T7/187 ,  G06V10/507 ,  G06F18/21355

摘要： The technology disclosed corrects inter-cluster intensity profile variation for improved base calling on a cluster-by-cluster basis. The technology disclosed accesses current intensity data and historic intensity data of a target cluster, where the current intensity data is for a current sequencing cycle and the historic intensity data is for one or more preceding sequencing cycles. A first accumulated intensity correction parameter is determined by accumulating distribution intensities measured for the target cluster at the current and preceding sequencing cycles. A second accumulated intensity correction parameter is determined by accumulating intensity errors measured for the target cluster at the current and preceding sequencing cycles. Based on the first and second accumulated intensity correction parameters, next intensity data for a next sequencing cycle is corrected to generate corrected next intensity data, which is used to base call the target cluster at the next sequencing cycle.

公开(公告)号：US11706492B1

公开(公告)日：2023-07-18

申请号：US17746771

申请日：2022-05-17

申请人： GENESIS LAB, INC.

发明人： Dae Hun Yoo ,  Young Bok Lee ,  Ji Hyeong Yoo

IPC分类号： H04N21/466 ,  G06F18/2135 ,  G06F18/22

CPC分类号： H04N21/4666 ,  G06F18/21355 ,  G06F18/22 ,  H04N21/4668

摘要： Disclosed are a method, a server and a computer-readable medium for recommending nodes of an interactive content, in which, when receiving recommendation request information for requesting a recommendation node for a specific node included in an interactive content from a user generating the interactive content, a first embedding value for a first set including the specific node is calculated, and a second embedding value for each second set including each of a plurality of nodes of each of one or more other interactive contents included in the service server is calculated, so as to calculate a similarity between the first embedding value and the second embedding value and provide the user with a next node, as a recommendation node, of a node corresponding to the second embedding value determined based on the similarity.

公开(公告)号：US11704559B2

公开(公告)日：2023-07-18

申请号：US16904460

申请日：2020-06-17

申请人： Adobe Inc.

发明人： John Collomosse

IPC分类号： G06N3/08 ,  G06N3/04 ,  G06F18/2135 ,  G06N3/045 ,  G06F8/38 ,  G06F16/583

CPC分类号： G06N3/08 ,  G06F8/38 ,  G06F16/583 ,  G06F18/21355 ,  G06N3/04 ,  G06N3/045

摘要： Embodiments are disclosed for learning structural similarity of user experience (UX) designs using machine learning. In particular, in one or more embodiments, the disclosed systems and methods comprise generating a representation of a layout of a graphical user interface (GUI), the layout including a plurality of control components, each control component including a control type, geometric features, and relationship features to at least one other control component, generating a search embedding for the representation of the layout using a neural network, and querying a repository of layouts in embedding space using the search embedding to obtain a plurality of layouts based on similarity to the layout of the GUI in the embedding space.

公开(公告)号：US12099929B2

公开(公告)日：2024-09-24

申请号：US18329072

申请日：2023-06-05

申请人： The MITRE Corporation

发明人： John C. Henderson ,  Lucy R. Chai ,  Jeffrey Zarrella ,  Abigail S. Gertner ,  Keith J. Miller

IPC分类号： G06N3/08 ,  G06F18/2135 ,  G06V10/82 ,  G06V30/19 ,  G06V40/16

CPC分类号： G06N3/08 ,  G06F18/21355 ,  G06V10/82 ,  G06V30/19173 ,  G06V40/172 ,  G06V40/179

摘要： Described are methods, systems, and computer-program product embodiments for selecting a face image based on a name. In some embodiments, a method includes receiving the name. Based on the name, a name vector is selected from a plurality of name vectors in a dataset that maps a plurality of names to a plurality of corresponding name vectors in a vector space, where each name vector includes representations associated with a plurality of words associated with each name. A plurality of face vectors corresponding to a plurality of face images is received. A face vector is selected from the plurality of face vectors based on a plurality of similarity scores calculated for the plurality of corresponding face vectors, where for each name vector, a similarity score is calculated based on the name vector and each face vector. The face image is output based on the selected face vector.

公开(公告)号：US20240296206A1

公开(公告)日：2024-09-05

申请号：US18616896

申请日：2024-03-26

申请人： Quantum-Si Incorporated

发明人： Umut Eser ,  Michael Meyer

IPC分类号： G06F18/25 ,  G06F18/2135 ,  G06F18/214 ,  G06F18/22

CPC分类号： G06F18/256 ,  G06F18/21355 ,  G06F18/214 ,  G06F18/22

摘要： Methods and apparatus for predicting an association between input data in a first modality and data in a second modality using a statistical model trained to represent interactions between data having a plurality of modalities including the first modality and the second modality, the statistical model comprising a plurality of encoders and decoders, each of which is trained to process data for one of the plurality of modalities, and a joint-modality representation coupling the plurality of encoders and decoders. The method comprises selecting, based on the first modality and the second modality, an encoder/decoder pair or a pair of encoders, from among the plurality of encoders and decoders, and processing the input data with the joint-modality representation and the selected encoder/decoder pair or pair of encoders to predict the association between the input data and the data in the second modality.

公开(公告)号：US20240078300A1

公开(公告)日：2024-03-07

申请号：US18140935

申请日：2023-04-28

申请人： Private Identity LLC

发明人： Scott Edward Streit

IPC分类号： G06F21/32 ,  G06F18/2135 ,  G06F21/60 ,  G06F21/62 ,  G06N3/02 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82 ,  G06V40/16 ,  H04L9/00 ,  H04L9/40

CPC分类号： G06F21/32 ,  G06F18/21355 ,  G06F21/602 ,  G06F21/6245 ,  G06N3/02 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G06V40/172 ,  H04L9/008 ,  H04L63/0428

摘要： In one embodiment, a set of feature vectors can be derived from any biometric data, and then using a deep neural network (“DNN”) on those one-way homomorphic encryptions (i.e., each biometrics' feature vector) can determine matches or execute searches on encrypted data. Each biometrics' feature vector can then be stored and/or used in conjunction with respective classifications, for use in subsequent comparisons without fear of compromising the original biometric data. In various embodiments, the original biometric data is discarded responsive to generating the encrypted values. In another embodiment, the homomorphic encryption enables computations and comparisons on cypher text without decryption. This improves security over conventional approaches. Searching biometrics in the clear on any system, represents a significant security vulnerability. In various examples described herein, only the one-way encrypted biometric data is available on a given device. Various embodiments restrict execution to occur on encrypted biometrics for any matching or searching.

公开(公告)号：US11853396B2

公开(公告)日：2023-12-26

申请号：US18154603

申请日：2023-01-13

申请人： Illumina, Inc.

发明人： Eric Jon Ojard ,  Abde Ali Hunaid Kagalwalla ,  Rami Mehio ,  Nitin Udpa ,  Gavin Derek Parnaby ,  John S Vieceli

IPC分类号： G06N3/08 ,  G06F18/2411 ,  G06T7/187 ,  G06V10/50 ,  G06F18/2135

CPC分类号： G06F18/2411 ,  G06F18/21355 ,  G06T7/187 ,  G06V10/507

摘要： The technology disclosed corrects inter-cluster intensity profile variation for improved base calling on a cluster-by-cluster basis. The technology disclosed accesses current intensity data and historic intensity data of a target cluster, where the current intensity data is for a current sequencing cycle and the historic intensity data is for one or more preceding sequencing cycles. A first accumulated intensity correction parameter is determined by accumulating distribution intensities measured for the target cluster at the current and preceding sequencing cycles. A second accumulated intensity correction parameter is determined by accumulating intensity errors measured for the target cluster at the current and preceding sequencing cycles. Based on the first and second accumulated intensity correction parameters, next intensity data for a next sequencing cycle is corrected to generate corrected next intensity data, which is used to base call the target cluster at the next sequencing cycle.

公开(公告)号：US11989933B2

公开(公告)日：2024-05-21

申请号：US16976412

申请日：2019-04-29

申请人： CARNEGIE MELLON UNIVERSITY

发明人： Felix Juefei Xu ,  Marios Savvides

IPC分类号： G06V10/82 ,  G06F18/21 ,  G06F18/2135 ,  G06F18/2413 ,  G06F18/25 ,  G06N3/045 ,  G06N3/048 ,  G06N3/08 ,  G06N3/084 ,  G06V10/44

CPC分类号： G06V10/82 ,  G06F18/21 ,  G06F18/21355 ,  G06F18/2414 ,  G06F18/253 ,  G06N3/045 ,  G06N3/048 ,  G06N3/08 ,  G06N3/084 ,  G06V10/454

摘要： The invention proposes a method of training a convolutional neural network in which, at each convolutional layer, weights for one seed convolutional filter per layer are updated during each training iteration. All other convolutional filters are polynomial transformations of the seed filter, or, alternatively, all response maps are polynomial transformations of the response map generated by the seed filter.

公开(公告)号：US11900686B1

公开(公告)日：2024-02-13

申请号：US17089269

申请日：2020-11-04

申请人： Amazon Technologies, Inc.

发明人： Zheshen Wang ,  Dimitris Papadimitriou ,  Mehran Kafai ,  Jarrod Sherwin ,  Anthony Sharma

IPC分类号： G06V20/56 ,  G06T11/00 ,  G06N20/00 ,  G06T7/00 ,  G06Q10/083 ,  G06F18/214 ,  G06F18/2431 ,  G06F18/2135

CPC分类号： G06V20/56 ,  G06F18/2148 ,  G06F18/21355 ,  G06F18/2431 ,  G06N20/00 ,  G06Q10/0838 ,  G06T7/0002 ,  G06T11/00 ,  G06T2207/30168 ,  G06T2210/12

摘要： Techniques for improving image processing related to item deliveries are described. In an example, a computer system receives an image showing a drop-off of an item, the item associated with a delivery to a delivery location. The computer system inputs the image to a first artificial intelligence (AI) model. The computer system receives first data comprising an indication of whether the drop-off is correct from the first AI model. The computer system causes a presentation of the indication at a device associated with the delivery of the item to the delivery location.