-
公开(公告)号：US20200311072A1
公开(公告)日：2020-10-01
申请号：US16819947
申请日：2020-03-16
Applicant: NEC Laboratories America, Inc.
Inventor： Eric Cosatto , Alexandru Niculescu-Mizil
IPC: G06F16/2452 , G06F16/242 , G06F16/901 , G06N7/00 , G06N20/00 , G06F40/205
Abstract: Systems and methods for solving queries on image data are provided. The system includes a processor device coupled to a memory device. The system includes a detector manager with a detector application programming interface (API) to allow external detectors to be inserted into the system by exposing capabilities of the external detectors and providing a predetermined way to execute the external detectors. An ontology manager exposes knowledge bases regarding ontologies to a reasoning engine. A query parser transforms a natural query into query directed acyclic graph (DAG). The system includes a reasoning engine that uses the query DAG, the ontology manager and the detector API to plan an execution list of detectors. The reasoning engine uses the query DAG, a scene representation DAG produced by the external detectors and the ontology manager to answer the natural query.
-
公开(公告)号：US20160328466A1
公开(公告)日：2016-11-10
申请号：US15148776
申请日：2016-05-06
Applicant: NEC Laboratories America, Inc.
Inventor： Alexandru Niculescu-Mizil , Mohammad Ehsan Abbasnejad
IPC: G06F17/30
CPC classification number: G06F17/30598
Abstract: Systems and methods for assigning labels to an object are provided. The method includes: receiving a set of labels and at least one object to be assigned labels; applying a label filter to the set of labels and to each of the at least one objects; identifying which labels in the set of labels are irrelevant; eliminating labels in the set of labels that are irrelevant to each of the at least one objects from further consideration; creating a subset of labels; determining which labels in the subset of labels are relevant to the object; assigning, to each of the at least one objects, the labels that are relevant to the object; determining which of the objects are relevant to a user to create user-oriented content, the user-oriented content consisting of at least one object determined to be relevant to a user; and displaying the user-orientated content to the user.
Abstract translation: 提供了将标签分配给对象的系统和方法。 该方法包括：接收一组标签和至少一个要分配标签的对象; 对所述一组标签和所述至少一个对象中的每一个应用标签过滤器; 识别该组标签中的哪些标签是不相关的; 从进一步的考虑中消除与所述至少一个对象中的每一个无关的标签组中的标签; 创建一个标签子集; 确定标签子集中的哪些标签与对象相关; 向所述至少一个对象中的每一个分配与所述对象相关的标签; 确定哪个对象与用户相关以创建面向用户的内容，所述面向用户的内容包括被确定为与用户相关的至少一个对象; 并向用户显示面向用户的内容。
-
公开(公告)号：US20130097108A1
公开(公告)日：2013-04-18
申请号：US13652087
申请日：2012-10-15
Applicant: NEC LABORATORIES AMERICA, INC.
Inventor： Alexandru Niculescu-Mizil , Abhishek Kumar , Koray Kavukcuoglu
IPC: G06F15/18
CPC classification number: G06N99/005
Abstract: Disclosed are methods and structures of Multiple Kernel learning framed as a standard binary classification problem with additional constraints that ensure the positive definiteness of the learned kernel. Advantageously, the disclosed methods and structures permit the use of binary classification technologies to develop better performing, and more scalable Multiple Kernel Learning methods that are conceptually simpler.
Abstract translation: 披露的是多核内核学习的方法和结构，被认为是标准的二进制分类问题，其附加约束可以确保学习内核的正确性。 有利地，所公开的方法和结构允许使用二进制分类技术来开发更好的执行和更可扩展的多内核学习方法，其在概念上更简单。
-
公开(公告)号：US20240378892A1
公开(公告)日：2024-11-14
申请号：US18654620
申请日：2024-05-03
Applicant: NEC Laboratories America, Inc.
Inventor： Iain Melvin , Alexandru Niculescu-Mizil , Deep Patel
Abstract: Systems and methods for optimizing multi-camera multi-entity artificial intelligence tracking systems. Visual and location information of entities from video feeds received from multiple cameras can be obtained by employing an entity detection model and re-identification model. Likelihood scores that entity detections belong to an entity track can be predicted from the visual and location information. The entity detections predicted into entity tracks can be processed by employing combinatorial optimization of the likelihood scores by identifying assumptions from the likelihood scores, entity detections, and the entity tracks, filtering the assumptions with unsatisfiable problems to obtain a filtered assumptions set, and optimizing an answer set by utilizing the filtered assumptions set and the likelihood scores to maximize an overall score and obtain optimized entity tracks. Multiple entities can be monitored by utilizing the optimized entity tracks.
-
公开(公告)号：US20240161313A1
公开(公告)日：2024-05-16
申请号：US18505732
申请日：2023-11-09
Applicant: NEC Laboratories America, Inc.
Inventor： Deep Patel , Alexandru Niculescu-Mizil , Iain Melvin , Seonghyeon Moon
CPC classification number: G06T7/248 , G06T7/292 , G06V10/82 , G06V20/41 , G06V20/52 , G06V40/10 , G16H15/00 , G16H40/67 , G06T2207/10016 , G06T2207/20081 , G06T2207/20084 , G06T2207/30004 , G06T2207/30196 , G06V2201/03
Abstract: Methods and systems for tracking movement include performing person detection in frames from multiple video streams to identify detection images. Visual and location information from the detection images are combined to generate scores for pairs of detection images across the multiple video streams and across frames of respective video streams. A pairwise detection graph is generated using the detection images as nodes and the scores as weighted edges. Movement of an individual is tracked based a constrained answer set programming problem, with constraints determined based on matching scores and logical assumptions. An action responsive to the tracked movement is performed. Tracking of movement of a patient in a healthcare facility can be used to inform treatment decisions by healthcare professionals.
-
Patent Agency Ranking
公开(公告)号：US20220101007A1
公开(公告)日：2022-03-31
申请号：US17463757
申请日：2021-09-01
Applicant: NEC Laboratories America, Inc.
Inventor： Asim Kadav , Farley Lai , Hans Peter Graf , Alexandru Niculescu-Mizil , Renqiang Min , Honglu Zhou
Abstract: A method for using a multi-hop reasoning framework to perform multi-step compositional long-term reasoning is presented. The method includes extracting feature maps and frame-level representations from a video stream by using a convolutional neural network (CNN), performing object representation learning and detection, linking objects through time via tracking to generate object tracks and image feature tracks, feeding the object tracks and the image feature tracks to a multi-hop transformer that hops over frames in the video stream while concurrently attending to one or more of the objects in the video stream until the multi-hop transformer arrives at a correct answer, and employing video representation learning and recognition from the objects and image context to locate a target object within the video stream.
-
公开(公告)号：US10964011B2
公开(公告)日：2021-03-30
申请号：US16703349
申请日：2019-12-04
Applicant: NEC Laboratories America, Inc.
Inventor： Eric Cosatto , Felix Wu , Alexandru Niculescu-Mizil
Abstract: A method is provided for model training to detect defective products. The method includes sampling training images of a product to (i) extract image portions therefrom made of a center patch and its context and (ii) black-out the center patch. The method further includes performing unsupervised back-propagation training of a Contextual Auto-Encoder (CAE) model using (i) the image portions with the blacked-out center patch as an input and, (ii) the center patch as a target output and, (iii) an image-based loss function, to obtain a trained CAE model. The method also includes sampling positive and negative center-patch-sized portions from the training images. The method additionally includes normalizing, using the trained CAE model, the positive and negative center-patch-sized portions. The method further includes performing supervised training of a classifier model using the normalized positive and negative center-patch-sized portions to obtain a trained supervised classifier model for detecting the defective products.
-
公开(公告)号：US20180374569A1
公开(公告)日：2018-12-27
申请号：US15983392
申请日：2018-05-18
Applicant: NEC Laboratories America, Inc.
Inventor： Alexandru Niculescu-Mizil , Eric Cosatto , Felix Wu
CPC classification number: G06T7/0008 , G06T7/001 , G06T7/0014 , G06T11/008 , G06T11/206 , G06T2207/10032 , G06T2207/10044 , G06T2207/10048 , G06T2207/10081 , G06T2207/10088 , G06T2207/10104 , G06T2207/10116 , G06T2207/10132 , G06T2207/20081 , G06T2207/20084 , G16H20/30 , G16H30/40 , G16H50/20 , G16H50/70 , H04N19/132 , H04N19/17
Abstract: Systems and methods for diagnosing a patient condition include a medical imaging device for generating an anatomical image. A reconstructor reconstructs the anatomical image by reconstructing portions of the anatomical image to be a healthy representation of the portions and merging the portions into the anatomical image to generate a reconstructed image. A contrastor contrasts the anatomical image with the reconstructed image to generate an anomaly map indicating locations of difference between the anatomical image and the reconstructed image. An anomaly tagging device tags the locations of difference as anomalies corresponding to anatomical abnormalities in the anatomical image, and a display displays the anatomical image with tags corresponding to the anatomical abnormalities.
-
公开(公告)号：US10162879B2
公开(公告)日：2018-12-25
申请号：US15148776
申请日：2016-05-06
Applicant: NEC Laboratories America, Inc.
Inventor： Alexandru Niculescu-Mizil , Mohammad Ehsan Abbasnejad
IPC: G06F17/30
Abstract: Systems and methods for assigning labels to an object are provided. A set of labels is assigned to at least one object. A label filter is applied to the set of labels and to the object and labels that are irrelevant to the object are identified by the label filter. The irrelevant labels are then eliminated from further consideration and a subset of labels are created. Labels from the subset of labels that are relevant to the object are then determined and assigned to the object. The elimination of the irrelevant labels increases the speed of the labeling process. A determination of which of the objects are relevant to a user may then be performed to create user-oriented content.
-
公开(公告)号：US08838508B2
公开(公告)日：2014-09-16
申请号：US13652087
申请日：2012-10-15
Applicant: NEC Laboratories America, Inc.
Inventor： Alexandru Niculescu-Mizil , Abhishek Kumar , Koray Kavukcuoglu
CPC classification number: G06N99/005
Abstract: Disclosed are methods and structures of Multiple Kernel learning framed as a standard binary classification problem with additional constraints that ensure the positive definiteness of the learned kernel. Advantageously, the disclosed methods and structures permit the use of binary classification technologies to develop better performing, and more scalable Multiple Kernel Learning methods that are conceptually simpler.
Abstract translation: 披露的是多核内核学习的方法和结构，被认为是标准的二进制分类问题，其附加约束可以确保学习内核的正确性。 有利地，所公开的方法和结构允许使用二进制分类技术来开发更好的性能和更可扩展的多内核学习方法，其在概念上更简单。
-
-
-
-
-
-
-
-
-
Search Results
31
records
(took 0.017 seconds)
