JP6998959B2 - 神経生理学的信号を使用する反復分類のためのシステムと方法 - Google Patents

神経生理学的信号を使用する反復分類のためのシステムと方法 Download PDF

Info

Publication number
JP6998959B2
JP6998959B2 JP2019533183A JP2019533183A JP6998959B2 JP 6998959 B2 JP6998959 B2 JP 6998959B2 JP 2019533183 A JP2019533183 A JP 2019533183A JP 2019533183 A JP2019533183 A JP 2019533183A JP 6998959 B2 JP6998959 B2 JP 6998959B2
Authority
JP
Japan
Prior art keywords
image
images
target
neural network
observer
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
JP2019533183A
Other languages
English (en)
Japanese (ja)
Other versions
JP2020502683A (ja
JP2020502683A5 (enExample
Inventor
アミール ビー ゲヴァ
エイタン ネッツァー
ラン エル マノール
セルゲイ ヴァイスマン
レオン ワイ デオウェル
ウリ アントマン
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Innereye Ltd
Original Assignee
Innereye Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Innereye Ltd filed Critical Innereye Ltd
Publication of JP2020502683A publication Critical patent/JP2020502683A/ja
Publication of JP2020502683A5 publication Critical patent/JP2020502683A5/ja
Application granted granted Critical
Publication of JP6998959B2 publication Critical patent/JP6998959B2/ja
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/015Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/21Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/23Clustering techniques
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/241Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2411Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/243Classification techniques relating to the number of classes
    • G06F18/2433Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/017Gesture based interaction, e.g. based on a set of recognized hand gestures
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • G06N20/20Ensemble learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks
    • G06N3/0455Auto-encoder networks; Encoder-decoder networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0464Convolutional networks [CNN, ConvNet]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/088Non-supervised learning, e.g. competitive learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/0895Weakly supervised learning, e.g. semi-supervised or self-supervised learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/09Supervised learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/091Active learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/20Image preprocessing
    • G06V10/255Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/44Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/778Active pattern-learning, e.g. online learning of image or video features
    • G06V10/7784Active pattern-learning, e.g. online learning of image or video features based on feedback from supervisors
    • G06V10/7788Active pattern-learning, e.g. online learning of image or video features based on feedback from supervisors the supervisor being a human, e.g. interactive learning with a human teacher
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20081Training; Learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20084Artificial neural networks [ANN]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30016Brain

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computing Systems (AREA)
  • Biomedical Technology (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • Molecular Biology (AREA)
  • Medical Informatics (AREA)
  • Mathematical Physics (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Human Computer Interaction (AREA)
  • Dermatology (AREA)
  • Neurology (AREA)
  • Neurosurgery (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Image Analysis (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
JP2019533183A 2016-12-21 2017-12-21 神経生理学的信号を使用する反復分類のためのシステムと方法 Active JP6998959B2 (ja)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201662437065P 2016-12-21 2016-12-21
US62/437,065 2016-12-21
PCT/IB2017/058297 WO2018116248A1 (en) 2016-12-21 2017-12-21 System and method for iterative classification using neurophysiological signals

Publications (3)

Publication Number Publication Date
JP2020502683A JP2020502683A (ja) 2020-01-23
JP2020502683A5 JP2020502683A5 (enExample) 2020-03-05
JP6998959B2 true JP6998959B2 (ja) 2022-01-18

Family

ID=62626017

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2019533183A Active JP6998959B2 (ja) 2016-12-21 2017-12-21 神経生理学的信号を使用する反復分類のためのシステムと方法

Country Status (7)

Country Link
US (2) US11580409B2 (enExample)
EP (1) EP3558102B1 (enExample)
JP (1) JP6998959B2 (enExample)
CN (1) CN110139597B (enExample)
CA (1) CA3046939A1 (enExample)
IL (1) IL267518B2 (enExample)
WO (1) WO2018116248A1 (enExample)

Families Citing this family (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3558102B1 (en) 2016-12-21 2024-11-20 Innereye Ltd. System and method for iterative classification using neurophysiological signals
US11586928B2 (en) * 2018-03-09 2023-02-21 Tata Consultancy Services Limited Method and system for incorporating regression into stacked auto encoder (SAE)
KR102695519B1 (ko) * 2018-07-02 2024-08-14 삼성전자주식회사 영상 모델 구축 장치 및 방법
GB2575852B (en) * 2018-07-26 2021-06-09 Advanced Risc Mach Ltd Image processing
US11158063B2 (en) * 2018-07-30 2021-10-26 Hewlett Packard Enterprise Development Lp Objects and features neural network
WO2020028352A1 (en) * 2018-07-31 2020-02-06 Washington University Methods and systems for segmenting organs in images using a cnn-based correction network
KR102608981B1 (ko) * 2018-10-24 2023-12-01 한국전자통신연구원 향 시각화 시스템 및 방법
US12114989B2 (en) 2018-12-04 2024-10-15 Brainvivo Ltd. Apparatus and method for utilizing a brain feature activity map database to characterize content
JP7103237B2 (ja) * 2019-01-09 2022-07-20 株式会社明電舎 流量予測装置及び流量予測方法
US11715043B2 (en) 2019-03-01 2023-08-01 Apple Inc. Semantics preservation for machine learning models deployed as dependent on other machine learning models
US10878298B2 (en) * 2019-03-06 2020-12-29 Adobe Inc. Tag-based font recognition by utilizing an implicit font classification attention neural network
US10984560B1 (en) * 2019-03-29 2021-04-20 Amazon Technologies, Inc. Computer vision using learnt lossy image compression representations
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
CN110084309B (zh) * 2019-04-30 2022-06-21 北京市商汤科技开发有限公司 特征图放大方法、装置和设备及计算机可读存储介质
US20210018896A1 (en) * 2019-07-16 2021-01-21 Carnegie Mellon University Methods and Systems for Noninvasive Mind-Controlled Devices
KR102758527B1 (ko) * 2019-10-29 2025-01-21 현대자동차주식회사 뇌파 신호를 이용한 이미지 생성 장치 및 방법
US11361189B2 (en) * 2019-12-03 2022-06-14 Ping An Technology (Shenzhen) Co., Ltd. Image generation method and computing device
CN111338482B (zh) * 2020-03-04 2023-04-25 太原理工大学 一种基于监督自编码的脑控字符拼写识别方法及系统
CN111783942B (zh) * 2020-06-08 2023-08-01 北京航天自动控制研究所 一种基于卷积循环神经网络的脑认知过程模拟方法
US20230419636A1 (en) * 2020-11-25 2023-12-28 Hewlett-Packard Development Company, L.P. Identifying anomaly location
KR20230131826A (ko) * 2021-01-14 2023-09-14 브레인비보 리미티드 일반 콘텐츠 뇌 반응 모델을 사용한 분야별 콘텐츠 분류
CN112800971B (zh) * 2021-01-29 2024-07-16 深圳市商汤科技有限公司 神经网络训练及点云数据处理方法、装置、设备和介质
US12412098B2 (en) 2021-03-04 2025-09-09 Samsung Electronics Co., Ltd. Apparatus and method for neural architecture searching with target data
CN113116306A (zh) * 2021-04-21 2021-07-16 复旦大学 一种基于听觉诱发脑电信号分析的意识障碍辅助诊断系统
CN113095297B (zh) * 2021-05-11 2022-07-15 昆明理工大学 一种基于一维投影跟踪眼动速率的疲劳检测方法
CN113995423B (zh) * 2021-06-21 2022-12-02 西安电子科技大学 基于相位保持网络的连续快速视觉演示脑电信号分类方法
CN114931388B (zh) * 2022-04-26 2024-11-01 广东医科大学 基于并行超顺磁聚类算法的神经元峰电位分类方法、装置、存储介质及计算机设备
EP4300265A1 (en) * 2022-06-29 2024-01-03 Copysan Communicaciones, SL Method, system and computer programs for the automatic labeling of images for defect detection
US20240160288A1 (en) * 2022-11-15 2024-05-16 Micron Technology, Inc. Neuronal to memory device communication
CN116383600A (zh) * 2023-03-16 2023-07-04 上海外国语大学 一种单试次脑电波信号分析方法和系统
CN117056831A (zh) * 2023-10-13 2023-11-14 南京龙垣信息科技有限公司 基于卷积神经网络的内心独白识别方法
CN117494061A (zh) * 2024-01-03 2024-02-02 中国科学院自动化研究所 用户兴趣挖掘方法、装置、电子设备及介质

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016193979A1 (en) 2015-06-03 2016-12-08 Innereye Ltd. Image classification by brain computer interface

Family Cites Families (39)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5513649A (en) 1994-03-22 1996-05-07 Sam Technology, Inc. Adaptive interference canceler for EEG movement and eye artifacts
US6278961B1 (en) * 1997-07-02 2001-08-21 Nonlinear Solutions, Inc. Signal and pattern detection or classification by estimation of continuous dynamical models
EP1743281A2 (en) * 2004-04-14 2007-01-17 Imperial Innovations Limited Estimation of within-class matrix in image classification
US8374687B2 (en) 2006-01-21 2013-02-12 Honeywell International Inc. Rapid serial visual presentation triage prioritization based on user state assessment
US8244475B2 (en) * 2007-12-27 2012-08-14 Teledyne Scientific & Imaging, Llc Coupling human neural response with computer pattern analysis for single-event detection of significant brain responses for task-relevant stimuli
JP5544620B2 (ja) * 2010-09-01 2014-07-09 独立行政法人産業技術総合研究所 意思伝達支援装置及び方法
US8792974B2 (en) 2012-01-18 2014-07-29 Brainscope Company, Inc. Method and device for multimodal neurological evaluation
US9269046B2 (en) 2012-01-18 2016-02-23 Brainscope Company, Inc. Method and device for multimodal neurological evaluation
US9111125B2 (en) * 2013-02-08 2015-08-18 Apple Inc. Fingerprint imaging and quality characterization
CN105051647B (zh) * 2013-03-15 2018-04-13 英特尔公司 基于生物物理信号的搜集时间和空间模式的大脑计算机接口(bci)系统
CA2909017C (en) 2013-04-14 2022-10-18 Yissum Research Development Company Of The Hebrew University Of Jerusalem Ltd. Classifying eeg signals in response to visual stimulus
TWI508702B (zh) 2013-07-10 2015-11-21 Univ Nat Chiao Tung 即時多通道自動眼動雜訊去除器
US9436279B2 (en) * 2014-03-31 2016-09-06 Rovi Guides, Inc. Systems and methods for controlling user devices based on brain activity
MX2016015708A (es) * 2014-05-30 2017-03-16 Univ Michigan Regents Interfaz cerebro-computadora para facilitar la seleccion directa de respuestas de opcion multiple y la identificacion de cambios de estado.
US10130813B2 (en) 2015-02-10 2018-11-20 Neuropace, Inc. Seizure onset classification and stimulation parameter selection
US11071501B2 (en) * 2015-08-14 2021-07-27 Elucid Bioiwaging Inc. Quantitative imaging for determining time to adverse event (TTE)
US10413724B2 (en) * 2015-10-23 2019-09-17 Hrl Laboratories, Llc Method for low latency automated closed-loop synchronization of neurostimulation interventions to neurophysiological activity
CN105868712A (zh) 2016-03-28 2016-08-17 中国人民解放军信息工程大学 基于后验概率模型的脑电与机器视觉目标图像检索方法
KR102707594B1 (ko) * 2016-11-11 2024-09-19 삼성전자주식회사 홍채 영역 추출 방법 및 장치
EP3558102B1 (en) 2016-12-21 2024-11-20 Innereye Ltd. System and method for iterative classification using neurophysiological signals
US10546242B2 (en) * 2017-03-03 2020-01-28 General Electric Company Image analysis neural network systems
US20190035113A1 (en) * 2017-07-27 2019-01-31 Nvidia Corporation Temporally stable data reconstruction with an external recurrent neural network
US11154251B2 (en) * 2018-02-10 2021-10-26 The Governing Council Of The University Of Toronto System and method for classifying time series data for state identification
WO2019213221A1 (en) 2018-05-01 2019-11-07 Blackthorn Therapeutics, Inc. Machine learning-based diagnostic classifier
EP3674994A1 (en) * 2018-12-27 2020-07-01 Bull SAS Method of blocking or passing messages sent via a firewall based on parsing of symbols strings contained in messages among different keywords
EP3674999A1 (en) * 2018-12-27 2020-07-01 Bull SAS Method of classification of images among different classes
US11423118B2 (en) * 2019-01-07 2022-08-23 Massachusetts Institute Of Technology Model agnostic time series analysis via matrix estimation
US11481578B2 (en) * 2019-02-22 2022-10-25 Neuropace, Inc. Systems and methods for labeling large datasets of physiological records based on unsupervised machine learning
US11562278B2 (en) * 2019-05-16 2023-01-24 Siemens Aktiengesellschaft Quantum machine learning algorithm for knowledge graphs
US10803646B1 (en) * 2019-08-19 2020-10-13 Neon Evolution Inc. Methods and systems for image and voice processing
US11593617B2 (en) * 2019-12-31 2023-02-28 X Development Llc Reservoir computing neural networks based on synaptic connectivity graphs
US11620487B2 (en) * 2019-12-31 2023-04-04 X Development Llc Neural architecture search based on synaptic connectivity graphs
WO2021195784A1 (en) * 2020-04-03 2021-10-07 Armstrong Caitrin Systems and methods for treatment selection
US11468288B2 (en) * 2020-07-28 2022-10-11 Oken Technologies, Inc. Method of and system for evaluating consumption of visual information displayed to a user by analyzing user's eye tracking and bioresponse data
US12354256B2 (en) * 2020-10-19 2025-07-08 Northwestern University Brain feature prediction using geometric deep learning on graph representations of medical image data
KR102321601B1 (ko) * 2020-11-19 2021-11-05 주식회사 휴런 뇌 영상을 이용한 알츠하이머병의 생물학적 분류 장치 및 방법
JP7552287B2 (ja) * 2020-11-25 2024-09-18 セイコーエプソン株式会社 物体検出方法、物体検出装置、及び、コンピュータープログラム
US20220301718A1 (en) * 2021-03-16 2022-09-22 Seshadri Paravastu System, Device, and Method of Determining Anisomelia or Leg Length Discrepancy (LLD) of a Subject by Using Image Analysis and Machine Learning
US11645836B1 (en) * 2022-06-30 2023-05-09 Intuit Inc. Adversarial detection using discriminator model of generative adversarial network architecture

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016193979A1 (en) 2015-06-03 2016-12-08 Innereye Ltd. Image classification by brain computer interface

Also Published As

Publication number Publication date
US20200193299A1 (en) 2020-06-18
IL267518B2 (en) 2024-04-01
CN110139597B (zh) 2022-12-30
US20230185377A1 (en) 2023-06-15
JP2020502683A (ja) 2020-01-23
EP3558102A4 (en) 2020-07-22
US12001607B2 (en) 2024-06-04
EP3558102B1 (en) 2024-11-20
IL267518B1 (en) 2023-12-01
IL267518A (en) 2019-08-29
EP3558102A1 (en) 2019-10-30
US11580409B2 (en) 2023-02-14
WO2018116248A1 (en) 2018-06-28
CA3046939A1 (en) 2018-06-28
CN110139597A (zh) 2019-08-16

Similar Documents

Publication Publication Date Title
JP6998959B2 (ja) 神経生理学的信号を使用する反復分類のためのシステムと方法
JP6959419B2 (ja) ブレインコンピュータインタフェースによる画像の分類
EP2986203B1 (en) Classifying eeg signals in response to visual stimulus
IL300879A (en) A method and system for quantifying attention
Ko et al. Semi-supervised deep adversarial learning for brain-computer interface
CN114564990A (zh) 一种基于多通道反馈胶囊网络的脑电信号分类方法
Abdullah et al. Assessment and Evaluation of cancer CT images using deep learning Techniques
Jayadurga et al. Leveraging Ensemble Techniques for Enhanced Eye State Classification with EEG Data
Karaduman et al. Determining the Demands of Disabled People by Artificial Intelligence Methods
Kardam et al. BSPKTM-SIFE-WST: bispectrum based channel selection using set-based-integer-coded fuzzy granular evolutionary algorithm and wavelet scattering transform for motor imagery EEG classification
CN112085057A (zh) 基于深度神经网络可视化的眼底图像生成方法及系统
Vishnupriya et al. Hyperband-Optimized 1D CNN for Automated Seizure Classification in EEG Signals
Azar MSCABiNET: A Lightweight Attention-Enhanced CNN-BiLSTM Model for EEG-Based Emotion Recognition
Ehtemami et al. Analyzing and Clustering of baseline and non-baseline EEG signal using MATLAB toolboxes

Legal Events

Date Code Title Description
RD01 Notification of change of attorney

Free format text: JAPANESE INTERMEDIATE CODE: A7426

Effective date: 20191030

A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A821

Effective date: 20191031

A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20191216

A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20191216

A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20210225

A131 Notification of reasons for refusal

Free format text: JAPANESE INTERMEDIATE CODE: A131

Effective date: 20210302

A601 Written request for extension of time

Free format text: JAPANESE INTERMEDIATE CODE: A601

Effective date: 20210526

A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20210901

TRDD Decision of grant or rejection written
A01 Written decision to grant a patent or to grant a registration (utility model)

Free format text: JAPANESE INTERMEDIATE CODE: A01

Effective date: 20211124

A61 First payment of annual fees (during grant procedure)

Free format text: JAPANESE INTERMEDIATE CODE: A61

Effective date: 20211221

R150 Certificate of patent or registration of utility model

Ref document number: 6998959

Country of ref document: JP

Free format text: JAPANESE INTERMEDIATE CODE: R150

R250 Receipt of annual fees

Free format text: JAPANESE INTERMEDIATE CODE: R250