JP2020511723A - 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習 - Google Patents

深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習 Download PDF

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JP2020511723A
JP2020511723A JP2019551365A JP2019551365A JP2020511723A JP 2020511723 A JP2020511723 A JP 2020511723A JP 2019551365 A JP2019551365 A JP 2019551365A JP 2019551365 A JP2019551365 A JP 2019551365A JP 2020511723 A JP2020511723 A JP 2020511723A
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ネヴェス，ルーカス
デビーシ，リアム
ヴェルサーチ，ヘザー・エイムズ
ワーブズ，ジェレミー
ゴルシェチニコフ，アナトリー
ヴェルサーチ，マッシミリアーノ
カッツ，ウォーレン
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ニューララ インコーポレイテッド
ニューララ インコーポレイテッド
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Priority to JP2023042142A priority Critical patent/JP7642009B2/ja
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JP2019551365A 2017-03-17 2018-03-19 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習 Pending JP2020511723A (ja)

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JP2023042142A JP7642009B2 (ja) 2017-03-17 2023-03-16 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習
JP2025027950A JP2025097996A (ja) 2017-03-17 2025-02-25 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習

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US201762472925P 2017-03-17 2017-03-17
US62/472,925 2017-03-17
PCT/US2018/023155 WO2018170512A1 (en) 2017-03-17 2018-03-19 Online, incremental real-time learning for tagging and labeling data streams for deep neural networks and neural network applications

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JP2023042142A Active JP7642009B2 (ja) 2017-03-17 2023-03-16 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習
JP2025027950A Pending JP2025097996A (ja) 2017-03-17 2025-02-25 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習

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JP2025027950A Pending JP2025097996A (ja) 2017-03-17 2025-02-25 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習

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US (2) US11410033B2 (https=)
EP (1) EP3596618A4 (https=)
JP (3) JP2020511723A (https=)
KR (1) KR20200023266A (https=)
CN (1) CN110651276A (https=)
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WO (1) WO2018170512A1 (https=)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2024512015A (ja) * 2021-03-22 2024-03-18 バーブ サージカル インコーポレイテッド 深層学習ベースのリアルタイム残存手術時間（ｒｓｄ）推定
JP2024532215A (ja) * 2021-08-31 2024-09-05 インターナショナル・ビジネス・マシーンズ・コーポレーション 機械学習用のコンピュータ・モデルの反復トレーニング

Families Citing this family (50)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2020511723A (ja) 2017-03-17 2020-04-16 ニューララ インコーポレイテッド 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習
US10223591B1 (en) 2017-03-30 2019-03-05 Amazon Technologies, Inc. Multi-video annotation
GB201810736D0 (en) * 2018-06-29 2018-08-15 Microsoft Technology Licensing Llc Neural trees
US10854006B2 (en) * 2018-11-15 2020-12-01 Palo Alto Research Center Incorporated AR-enabled labeling using aligned CAD models
US11182043B2 (en) 2018-11-27 2021-11-23 Anduril Industries Inc. Interactive virtual interface
US11562171B2 (en) 2018-12-21 2023-01-24 Osaro Instance segmentation by instance label factorization
CN111444746B (zh) * 2019-01-16 2024-01-30 北京亮亮视野科技有限公司 一种基于神经网络模型的信息标注方法
JP7233251B2 (ja) * 2019-02-28 2023-03-06 キヤノン株式会社 情報処理装置、情報処理装置の制御方法及びプログラム
US10878298B2 (en) 2019-03-06 2020-12-29 Adobe Inc. Tag-based font recognition by utilizing an implicit font classification attention neural network
GB2586198A (en) * 2019-03-08 2021-02-17 Tescap Ltd A monitoring and recording system
US11720621B2 (en) * 2019-03-18 2023-08-08 Apple Inc. Systems and methods for naming objects based on object content
US10803231B1 (en) * 2019-03-29 2020-10-13 Adobe Inc. Performing tag-based font retrieval using combined font tag recognition and tag-based font retrieval neural networks
CN110147547A (zh) * 2019-04-09 2019-08-20 苏宁易购集团股份有限公司 一种基于迭代式学习的智能辅助标注方法及系统
CA3139562A1 (en) * 2019-05-09 2020-11-12 Automobilia Ii, Llc Methods, systems and computer program products for media processing and display
CN111008706B (zh) * 2019-12-09 2023-05-05 长春嘉诚信息技术股份有限公司 一种自动标注、训练、预测海量数据的处理方法
EP4092555A4 (en) * 2020-01-17 2023-01-11 Fujitsu Limited CONTROL METHOD, INFORMATION PROCESSING DEVICE AND CONTROL PROGRAM
EP3869390B1 (de) * 2020-02-18 2025-07-23 dSPACE GmbH Computerimplementiertes verfahren und system zum erzeugen einer virtuellen fahrzeugumgebung
GB2593551A (en) * 2020-03-17 2021-09-29 Seechange Tech Limited Model-based machine-learning and inferencing
WO2021216439A1 (en) * 2020-04-20 2021-10-28 Chooch Intelligence Technologies Co. Automated generation of training data for contextually generated perceptions
US20230196632A1 (en) * 2020-05-26 2023-06-22 Sony Group Corporation Information processing device and information processing method
KR20220002007A (ko) 2020-06-30 2022-01-06 김현우 딥러닝 모델을 이용한 이미지 기반 안티 드론 감지 장치 및 방법
US11049044B1 (en) * 2020-07-07 2021-06-29 Blackshark.Ai Gmbh Visual image annotation utilizing machine learning for in-time feedback
CN111862045B (zh) * 2020-07-21 2021-09-07 上海杏脉信息科技有限公司 血管模型的生成方法及装置
KR20220020121A (ko) 2020-08-11 2022-02-18 삼성전자주식회사 컨텐트와 연관된 텍스트를 제공하기 위한 전자 장치 및 그 동작 방법
KR102427171B1 (ko) 2020-09-14 2022-07-29 (주)휴톰 영상 내의 객체 레이블링 제공 방법 및 이를 위한 장치
US11989262B2 (en) 2020-10-01 2024-05-21 Nvidia Corporation Unsupervised domain adaptation with neural networks
CN112270319B (zh) * 2020-11-10 2023-09-05 杭州海康威视数字技术股份有限公司 一种事件标注方法、装置及电子设备
CN112651938B (zh) * 2020-12-24 2023-12-19 平安科技（深圳）有限公司 视盘图像分类模型的训练方法、装置、设备及存储介质
CN112346074B (zh) * 2021-01-07 2021-04-20 北京海天瑞声科技股份有限公司 点云数据标注方法、点云数据标注装置及存储介质
US20220244727A1 (en) * 2021-02-01 2022-08-04 Nvidia Corporation Patching deployed deep neural networks for autonomous machine applications
TW202232437A (zh) * 2021-02-09 2022-08-16 阿物科技股份有限公司 圖像分類與標示方法及系統
US11410388B1 (en) * 2021-03-16 2022-08-09 Huawei Technologies Co., Ltd. Devices, systems, methods, and media for adaptive augmentation for a point cloud dataset used for training
KR102336962B1 (ko) 2021-05-11 2021-12-07 호서대학교 산학협력단 반-약 지도 학습을 통해 자동으로 라벨링을 수행하기 위한 장치 및 이를 위한 방법
KR102488619B1 (ko) * 2021-12-17 2023-01-18 주식회사 텐 학습된 인공 신경망을 자산화 하는 방법
KR102488618B1 (ko) * 2021-12-17 2023-01-18 주식회사 텐 인공 신경망의 학습을 위한 학습 데이터를 자산화 하는 방법
CN114429579B (zh) * 2022-01-29 2025-09-16 上海商汤临港智能科技有限公司 图像处理、分类方法及装置、电子设备及存储介质
US12159412B2 (en) * 2022-02-14 2024-12-03 Snap Inc. Interactively defining an object segmentation
KR102710479B1 (ko) * 2022-02-23 2024-09-25 한국항공대학교산학협력단 효율적인 주소 변환 기능을 구비한 신경망 추론 가속 장치 및 방법
US12265663B2 (en) 2022-04-04 2025-04-01 Snap Inc. Gesture-based application invocation
US20230343438A1 (en) * 2022-04-21 2023-10-26 Shanghai United Imaging Intelligence Co., Ltd. Systems and methods for automatic image annotation
US12282607B2 (en) 2022-04-27 2025-04-22 Snap Inc. Fingerspelling text entry
US20240078763A1 (en) * 2022-09-07 2024-03-07 Tomahawk Robotics, Inc. Architecture for distributed artificial intelligence augmentation
KR102822125B1 (ko) * 2022-12-08 2025-06-19 주식회사 에즈웰테크 클라우드 기반의 가상 컴퓨팅 작업 환경을 제공하는 클라우드 컴퓨팅 서비스를 운영하기 위한 클라우드 컴퓨팅 서비스 운영 서버
CN116503922A (zh) * 2022-12-20 2023-07-28 武汉虹信技术服务有限责任公司 一种用于人员居所精确定位的方法、系统及设备
US12499352B2 (en) * 2023-01-19 2025-12-16 Hong Kong Applied Science and Technology Research Institute Company Limited Anomaly detection with dynamic density estimation
US20240419726A1 (en) * 2023-06-15 2024-12-19 Adobe Inc. Learning to Personalize Vision-Language Models through Meta-Personalization
FR3153444A1 (fr) 2023-09-27 2025-03-28 Solystic Procédé d’entrainement pour un réseau de neurones destiné au contrôle de système de tri d’objets
WO2025119487A1 (en) * 2023-12-08 2025-06-12 Robert Bosch Gmbh Automated image annotation method and system
WO2025165371A1 (en) * 2024-02-02 2025-08-07 Hitachi Vantara Llc Intelligent tagging of structured and unstructured data
CN118445635B (zh) * 2024-05-17 2024-12-24 上海微创软件股份有限公司 一种人机协同的数据标注方法和系统

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090144772A1 (en) * 2007-11-30 2009-06-04 Google Inc. Video object tag creation and processing
US20120269436A1 (en) * 2011-04-20 2012-10-25 Xerox Corporation Learning structured prediction models for interactive image labeling
JP2015106197A (ja) * 2013-11-28 2015-06-08 キヤノン株式会社 画像処理装置、画像処理方法
US20150254555A1 (en) * 2014-03-04 2015-09-10 SignalSense, Inc. Classifying data with deep learning neural records incrementally refined through expert input

Family Cites Families (49)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7587101B1 (en) * 2005-02-28 2009-09-08 Adobe Systems Incorporated Facilitating computer-assisted tagging of object instances in digital images
US7831913B2 (en) * 2005-07-29 2010-11-09 Microsoft Corporation Selection-based item tagging
US8259995B1 (en) * 2006-01-26 2012-09-04 Adobe Systems Incorporated Designating a tag icon
US8165407B1 (en) 2006-10-06 2012-04-24 Hrl Laboratories, Llc Visual attention and object recognition system
US9361943B2 (en) * 2006-11-07 2016-06-07 The Board Of Trustees Of The Leland Stanford Jr. University System and method for tagging objects in a panoramic video and associating functions and indexing panoramic images with same
US7900225B2 (en) * 2007-02-20 2011-03-01 Google, Inc. Association of ads with tagged audiovisual content
DE112009000485T5 (de) * 2008-03-03 2011-03-17 VideoIQ, Inc., Bedford Objektvergleich für Verfolgung, Indizierung und Suche
JP2009229605A (ja) * 2008-03-19 2009-10-08 National Institute Of Advanced Industrial & Technology 活動プロセスリフレクション支援システム
US8176072B2 (en) * 2009-07-28 2012-05-08 Vulcan Technologies Llc Method and system for tag suggestion in a tag-associated data-object storage system
US9232211B2 (en) 2009-07-31 2016-01-05 The University Of Connecticut System and methods for three-dimensional imaging of objects in a scattering medium
US8270733B2 (en) 2009-08-31 2012-09-18 Behavioral Recognition Systems, Inc. Identifying anomalous object types during classification
US9031844B2 (en) 2010-09-21 2015-05-12 Microsoft Technology Licensing, Llc Full-sequence training of deep structures for speech recognition
US9336456B2 (en) * 2012-01-25 2016-05-10 Bruno Delean Systems, methods and computer program products for identifying objects in video data
IN2014DN08349A (https=) * 2012-03-15 2015-05-08 Behavioral Recognition Sys Inc
WO2013153883A1 (ja) * 2012-04-09 2013-10-17 ソニー株式会社 表示制御装置、表示制御方法、プログラム
EP2672396A1 (en) * 2012-06-08 2013-12-11 ETH Zürich Method for annotating images
US8879855B2 (en) 2012-08-17 2014-11-04 Nec Laboratories America, Inc. Image segmentation for large-scale fine-grained recognition
US9589595B2 (en) * 2013-12-20 2017-03-07 Qualcomm Incorporated Selection and tracking of objects for display partitioning and clustering of video frames
US9158971B2 (en) * 2014-03-03 2015-10-13 Xerox Corporation Self-learning object detectors for unlabeled videos using multi-task learning
US9626566B2 (en) 2014-03-19 2017-04-18 Neurala, Inc. Methods and apparatus for autonomous robotic control
US20150324686A1 (en) 2014-05-12 2015-11-12 Qualcomm Incorporated Distributed model learning
JP6629762B2 (ja) * 2014-05-23 2020-01-15 ベンタナ メディカル システムズ， インコーポレイテッド 画像内の生物学的構造及び／又はパターンの検出のためのシステム及び方法
JP6365024B2 (ja) * 2014-07-02 2018-08-01 富士通株式会社 サービス提供装置、方法、及びプログラム
US10289910B1 (en) * 2014-07-10 2019-05-14 Hrl Laboratories, Llc System and method for performing real-time video object recognition utilizing convolutional neural networks
US9396409B2 (en) * 2014-09-29 2016-07-19 At&T Intellectual Property I, L.P. Object based image processing
GB2532075A (en) * 2014-11-10 2016-05-11 Lego As System and method for toy recognition and detection based on convolutional neural networks
US9665802B2 (en) 2014-11-13 2017-05-30 Nec Corporation Object-centric fine-grained image classification
US9418319B2 (en) 2014-11-21 2016-08-16 Adobe Systems Incorporated Object detection using cascaded convolutional neural networks
US9767386B2 (en) * 2015-06-23 2017-09-19 Adobe Systems Incorporated Training a classifier algorithm used for automatically generating tags to be applied to images
US9633282B2 (en) 2015-07-30 2017-04-25 Xerox Corporation Cross-trained convolutional neural networks using multimodal images
US20170039469A1 (en) 2015-08-04 2017-02-09 Qualcomm Incorporated Detection of unknown classes and initialization of classifiers for unknown classes
US10331675B2 (en) * 2015-08-06 2019-06-25 Clarifai, Inc. Systems and methods for learning new trained concepts used to retrieve content relevant to the concepts learned
US10192129B2 (en) * 2015-11-18 2019-01-29 Adobe Systems Incorporated Utilizing interactive deep learning to select objects in digital visual media
US20180150695A1 (en) 2015-11-30 2018-05-31 Seematics Systems Ltd System and method for selective usage of inference models based on visual content
US11210595B2 (en) 2015-11-30 2021-12-28 Allegro Artificial Intelligence Ltd System and method for selective use of examples
US20170154269A1 (en) 2015-11-30 2017-06-01 Seematics Systems Ltd System and method for generating and using inference models
CN105718890A (zh) * 2016-01-22 2016-06-29 北京大学 一种基于卷积神经网络的特定视频检测方法
US9812175B2 (en) * 2016-02-04 2017-11-07 Gopro, Inc. Systems and methods for annotating a video
US10037471B2 (en) * 2016-07-05 2018-07-31 Nauto Global Limited System and method for image analysis
CN106203330A (zh) * 2016-07-08 2016-12-07 西安理工大学 一种基于卷积神经网络的车辆分类方法
US10051344B2 (en) * 2016-09-27 2018-08-14 Clarifai, Inc. Prediction model training via live stream concept association
US10346723B2 (en) * 2016-11-01 2019-07-09 Snap Inc. Neural network for object detection in images
US20180136332A1 (en) * 2016-11-15 2018-05-17 Wheego Electric Cars, Inc. Method and system to annotate objects and determine distances to objects in an image
US9754190B1 (en) 2016-11-29 2017-09-05 Seematics Systems Ltd System and method for image classification based on Tsallis entropy
US20180150698A1 (en) 2017-01-09 2018-05-31 Seematics Systems Ltd System and method for collecting information about repeated behavior
CN110574041B (zh) * 2017-02-23 2023-06-20 诺基亚技术有限公司 针对深度学习领域的协同激活
US10789291B1 (en) * 2017-03-01 2020-09-29 Matroid, Inc. Machine learning in video classification with playback highlighting
JP2020511723A (ja) 2017-03-17 2020-04-16 ニューララ インコーポレイテッド 深層ニューラルネットワークおよびニューラルネットワークアプリケーション向けのデータストリームのタグ付けおよびラベル付けのためのオンラインでのインクリメンタルリアルタイム学習
US20180373980A1 (en) * 2017-06-27 2018-12-27 drive.ai Inc. Method for training and refining an artificial intelligence

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090144772A1 (en) * 2007-11-30 2009-06-04 Google Inc. Video object tag creation and processing
US20120269436A1 (en) * 2011-04-20 2012-10-25 Xerox Corporation Learning structured prediction models for interactive image labeling
JP2015106197A (ja) * 2013-11-28 2015-06-08 キヤノン株式会社 画像処理装置、画像処理方法
US20150254555A1 (en) * 2014-03-04 2015-09-10 SignalSense, Inc. Classifying data with deep learning neural records incrementally refined through expert input

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2024512015A (ja) * 2021-03-22 2024-03-18 バーブ サージカル インコーポレイテッド 深層学習ベースのリアルタイム残存手術時間（ｒｓｄ）推定
JP7708354B2 (ja) 2021-03-22 2025-07-15 バーブ サージカル インコーポレイテッド 深層学習ベースのリアルタイム残存手術時間（ｒｓｄ）推定
JP2024532215A (ja) * 2021-08-31 2024-09-05 インターナショナル・ビジネス・マシーンズ・コーポレーション 機械学習用のコンピュータ・モデルの反復トレーニング

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