CN115087988A - 用于编码神经网络参数的构思 - Google Patents

用于编码神经网络参数的构思 Download PDF

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Publication number
CN115087988A
CN115087988A CN202080094840.2A CN202080094840A CN115087988A CN 115087988 A CN115087988 A CN 115087988A CN 202080094840 A CN202080094840 A CN 202080094840A CN 115087988 A CN115087988 A CN 115087988A
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neural network
network parameter
reconstruction
quantization
group
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保罗·海濑
汉勒·科什弗
海科·施瓦茨
德特勒夫·马尔佩
托马斯·威甘德
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Fraunhofer Gesellschaft zur Foerderung der Angewandten Forschung eV
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Fraunhofer Gesellschaft zur Foerderung der Angewandten Forschung eV
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    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
    • H04L47/2483—Traffic characterised by specific attributes, e.g. priority or QoS involving identification of individual flows
    • 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
    • G06N3/0495—Quantised networks; Sparse networks; Compressed 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/13—Adaptive entropy coding, e.g. adaptive variable length coding [AVLC] or context adaptive binary arithmetic coding [CABAC]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards

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  • Engineering & Computer Science (AREA)
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  • Biomedical Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
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  • Software Systems (AREA)
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  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Signal Processing (AREA)
  • Multimedia (AREA)
  • Neurology (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
  • Executing Machine-Instructions (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
CN202080094840.2A 2019-12-20 2020-12-21 用于编码神经网络参数的构思 Pending CN115087988A (zh)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
EP19218862 2019-12-20
EP19218862.1 2019-12-20
PCT/EP2020/087489 WO2021123438A1 (en) 2019-12-20 2020-12-21 Concepts for coding neural networks parameters

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CN115087988A true CN115087988A (zh) 2022-09-20

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US (2) US20220393986A1 (https=)
EP (1) EP4078454A1 (https=)
JP (2) JP7640552B2 (https=)
KR (1) KR20220127261A (https=)
CN (1) CN115087988A (https=)
WO (1) WO2021123438A1 (https=)

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US11037330B2 (en) * 2017-04-08 2021-06-15 Intel Corporation Low rank matrix compression
CN115699020A (zh) * 2020-06-05 2023-02-03 华为技术有限公司 用于神经网络的量化
US12363310B2 (en) * 2020-06-16 2025-07-15 Nokia Technologies Oy Guided probability model for compressed representation of neural networks
US20230229894A1 (en) * 2020-06-25 2023-07-20 Intellectual Discovery Co., Ltd. Method and apparatus for compression and training of neural network
WO2022139438A1 (ko) * 2020-12-22 2022-06-30 인텔렉추얼디스커버리 주식회사 딥러닝 기반 이미지 코딩 방법 및 장치
JP7325015B2 (ja) * 2021-03-24 2023-08-14 パナソニックＩｐマネジメント株式会社 量子化方法、量子化装置、及び、プログラム
US11909975B2 (en) * 2021-06-18 2024-02-20 Tencent America LLC Dependent scalar quantization with substitution in neural image compression
CN118140458A (zh) * 2021-10-13 2024-06-04 谷歌有限责任公司 量化的机器学习配置信息
KR20240132484A (ko) * 2022-01-09 2024-09-03 프라운호퍼 게젤샤프트 쭈르 푀르데룽 데어 안겐반텐 포르슝 에. 베. 신경 네트워크 파라미터를 인코딩 및 디코딩하는 컨셉
WO2024013109A1 (en) * 2022-07-11 2024-01-18 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Encoder, decoder and methods for coding a data structure
KR20250047001A (ko) * 2023-09-27 2025-04-03 삼성전자주식회사 심층 신경망 모델을 포함하는 전자 장치 및 그 동작 방법

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Publication number Priority date Publication date Assignee Title
AU2006201490B2 (en) * 2005-04-19 2008-05-22 Samsung Electronics Co., Ltd. Method and apparatus for adaptively selecting context model for entropy coding
US7894523B2 (en) * 2005-09-05 2011-02-22 Lg Electronics Inc. Method for modeling coding information of a video signal for compressing/decompressing coding information
US9584802B2 (en) * 2012-04-13 2017-02-28 Texas Instruments Incorporated Reducing context coded and bypass coded bins to improve context adaptive binary arithmetic coding (CABAC) throughput
CA2807908A1 (en) * 2012-06-30 2013-12-30 Research In Motion Limited Position-based context selection for greater-than-one flag decoding and encoding
CN112236999B (zh) * 2018-03-29 2022-12-13 弗劳恩霍夫应用研究促进协会 依赖性量化
US11451840B2 (en) * 2018-06-18 2022-09-20 Qualcomm Incorporated Trellis coded quantization coefficient coding
TW202601464A (zh) 2019-10-01 2026-01-01 弗勞恩霍夫爾協會 用於編/解碼神經網路參數之設備與方法、及相關資料串流與電腦程式

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JP2025016517A (ja) 2025-02-04
JP2023507502A (ja) 2023-02-22
US20250343764A1 (en) 2025-11-06
EP4078454A1 (en) 2022-10-26
KR20220127261A (ko) 2022-09-19
WO2021123438A1 (en) 2021-06-24
JP7640552B2 (ja) 2025-03-05
JP7783376B2 (ja) 2025-12-09
US20220393986A1 (en) 2022-12-08

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