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GB/T 45225-2025 English PDF

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US$679.00 · In stock
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GB/T 45225-2025: Artificial intelligence - Deep learning algorithms evaluation
Status: Valid

Standard ID	USD	BUY PDF	Lead-Days	Standard Title (Description)	Status
GB/T 45225-2025	679	Add to Cart	6 days	Artificial intelligence - Deep learning algorithms evaluation	Valid

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Basic data

Standard ID: GB/T 45225-2025 (GB/T45225-2025)
Description (Translated English): Artificial intelligence - Deep learning algorithms evaluation
Sector / Industry: National Standard (Recommended)
Classification of Chinese Standard: L79
Classification of International Standard: 35.100.05
Word Count Estimation: 34,344
Date of Issue: 2025-01-24
Date of Implementation: 2025-01-24
Issuing agency(ies): State Administration for Market Regulation, China National Standardization Administration

GB/T 45225-2025: Artificial intelligence - Deep learning algorithms evaluation

---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.
ICS 35.100.05 CCSL79 National Standard of the People's Republic of China Artificial Intelligence Deep Learning Algorithm Evaluation Released on 2025-01-24 2025-01-24 Implementation State Administration for Market Regulation The National Standardization Administration issued

Preface III 1 Scope 1 2 Normative references 1 3 Terms and Definitions 1 4 Evaluation Index System 2 5 Assessment Level 7 6 Evaluation Process 8 Appendix A (Informative) Selection of Deep Learning Algorithm Evaluation Indicators and Threshold Setting 17 Appendix B (Informative) Method for calculating weights of deep learning algorithm evaluation indicators 21 Appendix C (Informative) Deep Learning Algorithm Evaluation Implementation Case 24 Reference 26

Foreword

This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for standardization work Part 1.Structure and drafting rules for standardization documents" Drafting. Please note that some of the contents of this document may involve patents. The issuing organization of this document does not assume the responsibility for identifying patents. This document was proposed and coordinated by the National Technical Committee for Information Technology Standardization (SAC/TC28). The drafting units of this document are. China Electronics Technology Standardization Institute, Institute of Software, Chinese Academy of Sciences, Nanjing Software Technology Research Institute Institute of Aeronautics and Astronautics, Beijing University of Aeronautics and Astronautics, Beijing Software Product Quality Inspection and Testing Center Co., Ltd., Beijing Institute of Aerospace Automatic Control, China South Power Grid Co., Ltd. Ultra-high Voltage Transmission Company, Shanghai Computer Software Technology Development Center, University of Science and Technology of China, Beijing Eyesight Technology Co., Ltd., Shanghai SenseTime Intelligent Technology Co., Ltd., Denso Intelligent Technology (Shanghai) Co., Ltd., China Electronics Technology Group Corporation Big Data Research Institute Co., Ltd., Inspur Electronic Information Industry Co., Ltd., China Mobile Communications Group Co., Ltd., Beijing Shengzhi Technology Co., Ltd., GRG Banking Group Co., Ltd., Shanghai Wenyu Information Technology Co., Ltd., Hangzhou Hikvision Digital Technology Co., Ltd., CASCO Signal Co., Ltd. Alibaba Cloud Computing Co., Ltd., Tianjin (Binhai) Artificial Intelligence Innovation Center, China Ordnance Industry Information Center, Shanghai Enflame Technology Co., Ltd. Co., Ltd., Shanghai Artificial Intelligence Industry Association, Shenzhen Yuntian Lifei Technology Co., Ltd., Sichuan Changhong Electronics Holding Group Co., Ltd., China Shipbuilding Industry Corporation Comprehensive Technical and Economic Research Institute, Beijing Institute of Computer Technology and Applications, Hong Kong University of Science and Technology, Chinese Academy of Sciences Institute of Space Application Engineering and Technology, Zhejiang University, Shenyang Aircraft Design and Research Institute of Aviation Industry Corporation of China, Beijing University of Posts and Telecommunications, NARI Group Co., Ltd., Chongqing Guoke Chuzhi Information Technology Co., Ltd., Guoke Chushi (Chongqing) Software Co., Ltd., Chongqing Construction Industry (Group) Limited Liability Company. The main drafters of this document are. Bao Wei, Ye Heng, Meng Lingzhong, Xue Yunzhi, Ma Chenghao, Gao Hui, Liu Xianglong, Kong Hao, Wang Yang, Wang Ning, Chen Wenjie, Zhang Lan, Yang Chunlin, Wu Geng, Zhu Jian, Dong Qian, Yang Guang, Cai Huimin, Du Guoguang, Wang Kechen, Nie Jinran, Chen Xiaoliang, Xu Tianshi, Rui Ziwen, Ren Wenqi, Zhou Tingliang, Wu Tao, Shi Dianxi, Xie Wandong, Mei Jingqing, Chen Xi, Rao Xue, Cao Yu, Wu Lijin, Xu Zhewei, Song Jinke, Liu Aishan, Guo Jinyang, Wang Jinbo, Ji Shouling, Wen Xiaoling, Cheng Xiang, Chen Wei, Hu Yanling, Luo Yongjun, Zhang Yang. Artificial Intelligence Deep Learning Algorithm Evaluation

1 Scope

This document establishes an evaluation index system for artificial intelligence deep learning algorithms and describes evaluation methods, etc. This document is intended to guide deep learning algorithm developers, users, third parties and other related organizations to deep learning algorithms and their training. The obtained deep learning model is used for evaluation.

2 Normative references

The contents of the following documents constitute the essential clauses of this document through normative references in this document. For referenced documents without a date, only the version corresponding to that date applies to this document; for referenced documents without a date, the latest version (including all amendments) applies to This document. GB/T 35273-2020 Information security technology Personal information security specification GB/T 40660-2021 Information security technology Basic requirements for biometric information protection GB/T 41867-2022 Information Technology Artificial Intelligence Terminology

3 Terms and definitions

The terms and definitions defined in GB/T 41867-2022 and the following apply to this document. 3.1 Deep learning A method for creating rich hierarchical representations by training neural networks with many hidden layers. Note. Deep learning is a subset of machine learning. [Source. GB/T 41867-2022, 3.2.27] 3.2 A code snippet that uses a deep neural network structure to learn and reason to complete a specific function. 3.3 deep learning model deeplearningmodel A mathematical framework that produces inferences or predictions based on input data or information. 3.4 Test datatestdata Data used to evaluate the performance of the final machine learning model. [Source. GB/T 41867-2022, 3.2.3] 3.5 Adversarial examples Adding input samples formed by slight interference in the data set can induce the deep learning algorithm to give wrong output with a high probability, or even is to give a specific result. ......

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Tips & Frequently Asked Questions:

Question 1: How long will the true-PDF of GB/T 45225-2025_English be delivered?

Answer: Upon your order, we will start to translate GB/T 45225-2025_English as soon as possible, and keep you informed of the progress. The lead time is typically 4 ~ 6 working days. The lengthier the document the longer the lead time.

Question 2: Can I share the purchased PDF of GB/T 45225-2025_English with my colleagues?

Answer: Yes. The purchased PDF of GB/T 45225-2025_English will be deemed to be sold to your employer/organization who actually pays for it, including your colleagues and your employer's intranet.

Question 3: Does the price include tax/VAT?

Answer: Yes. Our tax invoice, downloaded/delivered in 9 seconds, includes all tax/VAT and complies with 100+ countries' tax regulations (tax exempted in 100+ countries) -- See Avoidance of Double Taxation Agreements (DTAs): List of DTAs signed between Singapore and 100+ countries

Question 4: Do you accept my currency other than USD?

Answer: Yes. If you need your currency to be printed on the invoice, please write an email to Sales@ChineseStandard.net. In 2 working-hours, we will create a special link for you to pay in any currencies. Otherwise, follow the normal steps: Add to Cart -- Checkout -- Select your currency to pay.