DE102020129251A1 - Adaptives verformbares kernvorhersagenetzwerk zum bildentrauschen - Google Patents

Adaptives verformbares kernvorhersagenetzwerk zum bildentrauschen Download PDF

Info

Publication number
DE102020129251A1
DE102020129251A1 DE102020129251.1A DE102020129251A DE102020129251A1 DE 102020129251 A1 DE102020129251 A1 DE 102020129251A1 DE 102020129251 A DE102020129251 A DE 102020129251A DE 102020129251 A1 DE102020129251 A1 DE 102020129251A1
Authority
DE
Germany
Prior art keywords
graphics
pixel
processor
memory
data
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.)
Pending
Application number
DE102020129251.1A
Other languages
German (de)
English (en)
Inventor
Anbang Yao
Ming Lu
Yikai Wang
Xiaoming Chen
Junjie Huang
Tao Lv
Yuanke Luo
Yi Yang
Feng Chen
Zhiming Wang
Zhiqiao Zheng
Shandong WANG
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.)
Intel Corp
Original Assignee
Intel Corp
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 Intel Corp filed Critical Intel Corp
Publication of DE102020129251A1 publication Critical patent/DE102020129251A1/de
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G06T1/20—Processor architectures; Processor configuration, e.g. pipelining
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
    • G06F9/38—Concurrent instruction execution, e.g. pipeline or look ahead
    • G06F9/3802—Instruction prefetching
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
    • G06F9/38—Concurrent instruction execution, e.g. pipeline or look ahead
    • G06F9/3802—Instruction prefetching
    • G06F9/3804—Instruction prefetching for branches, e.g. hedging, branch folding
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
    • G06F9/38—Concurrent instruction execution, e.g. pipeline or look ahead
    • G06F9/3885—Concurrent instruction execution, e.g. pipeline or look ahead using a plurality of independent parallel functional units
    • G06F9/3887—Concurrent instruction execution, e.g. pipeline or look ahead using a plurality of independent parallel functional units controlled by a single instruction for multiple data lanes [SIMD]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G06T3/4046—Scaling of whole images or parts thereof, e.g. expanding or contracting using neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/60—Image enhancement or restoration using machine learning, e.g. neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20024—Filtering details
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Molecular Biology (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Computational Linguistics (AREA)
  • Neurology (AREA)
  • Image Processing (AREA)
  • Image Generation (AREA)
  • Facsimile Image Signal Circuits (AREA)
DE102020129251.1A 2019-11-07 2020-11-06 Adaptives verformbares kernvorhersagenetzwerk zum bildentrauschen Pending DE102020129251A1 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201911081492.0A CN112785486A (zh) 2019-11-07 2019-11-07 用于图像去噪声的自适应可变形核预测网络
CN201911081492.0 2019-11-07

Publications (1)

Publication Number Publication Date
DE102020129251A1 true DE102020129251A1 (de) 2021-05-12

Family

ID=75584071

Family Applications (1)

Application Number Title Priority Date Filing Date
DE102020129251.1A Pending DE102020129251A1 (de) 2019-11-07 2020-11-06 Adaptives verformbares kernvorhersagenetzwerk zum bildentrauschen

Country Status (5)

Country Link
US (2) US11869171B2 (https=)
JP (1) JP2021077343A (https=)
KR (1) KR20210055583A (https=)
CN (1) CN112785486A (https=)
DE (1) DE102020129251A1 (https=)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11869171B2 (en) 2019-11-07 2024-01-09 Intel Corporation Adaptive deformable kernel prediction network for image de-noising

Families Citing this family (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021093958A1 (en) * 2019-11-14 2021-05-20 Huawei Technologies Co., Ltd. Spatially adaptive image filtering
US11539623B2 (en) 2020-08-31 2022-12-27 Micron Technology, Inc. Single field for encoding multiple elements
US11418455B2 (en) 2020-08-31 2022-08-16 Micron Technology, Inc. Transparent packet splitting and recombining
US11296995B2 (en) 2020-08-31 2022-04-05 Micron Technology, Inc. Reduced sized encoding of packet length field
US11360920B2 (en) 2020-08-31 2022-06-14 Micron Technology, Inc. Mapping high-speed, point-to-point interface channels to packet virtual channels
US11412075B2 (en) 2020-08-31 2022-08-09 Micron Technology, Inc. Multiple protocol header processing
US11871145B2 (en) * 2021-04-06 2024-01-09 Adobe Inc. Optimization of adaptive convolutions for video frame interpolation
US12283028B2 (en) * 2021-06-02 2025-04-22 Nvidia Corporation Spatio-temporal noise masks for image processing
CN113516235B (zh) * 2021-07-13 2024-10-18 南京大学 一种可变形卷积加速器和可变形卷积加速方法
CN113744156B (zh) * 2021-09-06 2022-08-19 中南大学 一种基于可变形卷积神经网络的图像去噪方法
KR102785795B1 (ko) * 2021-09-13 2025-03-26 삼성전자주식회사 대조도 조절 방법 및 이를 이용하는 장치
CN113689359B (zh) * 2021-09-23 2024-05-14 上海联影医疗科技股份有限公司 一种图像伪影去除模型及其训练方法和系统
CN117561537A (zh) 2021-10-07 2024-02-13 三星电子株式会社 显示设备及其操作方法
IT202100026552A1 (it) * 2021-10-18 2023-04-18 Durst Group Ag "Metodo e prodotto per la sintesi di dati di stampa e per la fornitura degli stessi ad una stampante"
CN113963009B (zh) * 2021-12-22 2022-03-18 中科视语(北京)科技有限公司 基于可形变划块的局部自注意力的图像处理方法和系统
US12462337B2 (en) * 2022-02-25 2025-11-04 Arm Limited System, devices and/or processes for processing image pixel values
CN114998964B (zh) * 2022-06-02 2023-04-18 天津道简智创信息科技有限公司 一种新型证照质量检测方法
GB2620920B (en) * 2022-07-21 2024-09-25 Advanced Risc Mach Ltd System, devices and/or processes for application of kernel coefficients
US12008728B2 (en) * 2022-08-31 2024-06-11 Qualcomm Incorporated Apparatuses and methods for processing single instruction for image transformation from non-integral locations
CN115661784B (zh) * 2022-10-12 2023-08-22 北京惠朗时代科技有限公司 一种面向智慧交通的交通标志图像大数据识别方法与系统
CN116363480B (zh) * 2023-03-20 2026-03-31 南京大学 一种用于图像像素处理网络的计算装置和方法
CN119313587B (zh) * 2024-12-18 2025-03-28 浙江大华技术股份有限公司 基于块匹配的图像降噪方法、设备及存储介质

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7873812B1 (en) 2004-04-05 2011-01-18 Tibet MIMAR Method and system for efficient matrix multiplication in a SIMD processor architecture
US7747070B2 (en) * 2005-08-31 2010-06-29 Microsoft Corporation Training convolutional neural networks on graphics processing units
US10223333B2 (en) 2014-08-29 2019-03-05 Nvidia Corporation Performing multi-convolution operations in a parallel processing system
US10402700B2 (en) * 2016-01-25 2019-09-03 Deepmind Technologies Limited Generating images using neural networks
US10997496B2 (en) 2016-08-11 2021-05-04 Nvidia Corporation Sparse convolutional neural network accelerator
US10891538B2 (en) 2016-08-11 2021-01-12 Nvidia Corporation Sparse convolutional neural network accelerator
US11531852B2 (en) * 2016-11-28 2022-12-20 D-Wave Systems Inc. Machine learning systems and methods for training with noisy labels
US10586310B2 (en) * 2017-04-06 2020-03-10 Pixar Denoising Monte Carlo renderings using generative adversarial neural networks
US10475165B2 (en) * 2017-04-06 2019-11-12 Disney Enterprises, Inc. Kernel-predicting convolutional neural networks for denoising
US10296578B1 (en) * 2018-02-20 2019-05-21 Paycor, Inc. Intelligent extraction and organization of data from unstructured documents
CN112785486A (zh) 2019-11-07 2021-05-11 英特尔公司 用于图像去噪声的自适应可变形核预测网络
US11676248B2 (en) * 2020-01-23 2023-06-13 Baidu Usa Llc Deep residual network for color filter array image denoising
EP4016446B1 (en) * 2020-12-21 2025-06-25 Dassault Systèmes Intelligent denoising
CN114693850A (zh) * 2020-12-25 2022-07-01 英特尔公司 用于图像和视频处理的条件核预测网络和自适应深度预测

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11869171B2 (en) 2019-11-07 2024-01-09 Intel Corporation Adaptive deformable kernel prediction network for image de-noising

Also Published As

Publication number Publication date
US20210142448A1 (en) 2021-05-13
KR20210055583A (ko) 2021-05-17
US20240127408A1 (en) 2024-04-18
CN112785486A (zh) 2021-05-11
US11869171B2 (en) 2024-01-09
JP2021077343A (ja) 2021-05-20

Similar Documents

Publication Publication Date Title
DE102020129251A1 (de) Adaptives verformbares kernvorhersagenetzwerk zum bildentrauschen
DE102020130078A1 (de) Systolische arithmetik an spärlichen daten
DE102020130073A1 (de) Verbesserung der datenlokalität für grafikprozessoreinheiten
DE112020001249T5 (de) Dünnbesetzt-Optimierungen für eine Matrixbeschleunigerarchitektur
DE102020129969A1 (de) Verbesserungen der verarbeitung und des caching von graphikverarbeitungseinheiten
DE112020001256T5 (de) Kompressionstechniken
DE102020129970A1 (de) Systeme und verfahren zur fehlererkennung und steuerung für eingebettete arbeitsspeicher- und rechenelemente
DE102020115026A1 (de) Systeme und Verfahren zur Tonabbildung von Bildern mit hohem Dynamikumfang für auf tiefem Lernen basierende Verarbeitung von hoher Qualität
DE112020000902T5 (de) Datenvorabruf für die grafikdatenverarbeitung
DE112020000854T5 (de) Thread-gruppen-planung für die grafikverarbeitung
DE102020132272A1 (de) Verfahren und vorrichtung zum codieren basierend auf schattierungsraten
DE102018110380A1 (de) Tool zum Ermöglichen der Effizienz beim Maschinenlernen
DE112020000464T5 (de) Mehrfachkachel-grafikprozessor-rendering
DE102020131896A1 (de) Deep learning-basierte auswahl von abtastwerten für adaptives supersampling
DE102022125592A1 (de) Erweitern von zeitlichen Anti-Aliasing mit neuronalem Netzwerk zur Historienvalidierung
DE102018110371A1 (de) Intelligente speicherhandhabung und datenmanagement für maschinenlernnetzwerke
DE102020130184A1 (de) Optimierungsmechanismus mit spärlich besetzten matrizen
DE102020129432A1 (de) System und Verfahren zum Anpassen eines ausführbaren Objekts an eine Verarbeitungseinheit
DE102020107080A1 (de) Grafiksysteme und Verfahren zum Beschleunigen von Synchronisation mittels feinkörniger Abhängigkeitsprüfung und Planungsoptimierungen basierend auf verfügbarem gemeinsam genutztem Speicherplatz
DE102020108476A1 (de) Mechanismus zum Ausführen nichtlinearer Funktionen in einem Beschleuniger des maschinellen Lernens
DE102020130865A1 (de) Anweisungen und logik für vektor-multiplikation-addition mit zero-skipping
DE102020130081A1 (de) Erweiterte prozessorfunktionen für berechnungen
DE102022125258A1 (de) Temporale Gradienten von Effekten höherer Ordnung zur Führung temporaler Akkumulation
DE102020130995A1 (de) Verfahren und vorrichtung zur codierung basierend auf wichtigkeitswerten
DE112022004016T5 (de) Zeitlich amortisierte Überabtastung unter Verwendung eines faltenden neuronalen Netzwerks mit gemischter Genauigkeit