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IEEE Recommended Practice for Framework and Process for Deep Learning Evaluation
IEEE Std 2841-2022
Year: 2023
Abstract: The recommendations on evaluating and improving algorithm reliability for shortening the development cycle of deep learning algorithms and improving the quality of software systems based on deep learning algorithms are defined in this document. An assessment index system and corresponding assessment process are specified in this document.
Subject: IEEE 2841
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IEEE Recommended Practice for Framework and Process for Deep Learning Evaluation
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| contributor author | IEEE - The Institute of Electrical and Electronics Engineers, Inc. | |
| date accessioned | 2023-08-07T18:47:01Z | |
| date available | 2023-08-07T18:47:01Z | |
| date copyright | 10 April 2023 | |
| date issued | 2023 | |
| identifier other | 10097701.pdf | |
| identifier uri | http://yse.yabesh.ir/std;query=autho47037D83FCDCAC4261598F1EFDEC014A/handle/yse/329675 | |
| description abstract | The recommendations on evaluating and improving algorithm reliability for shortening the development cycle of deep learning algorithms and improving the quality of software systems based on deep learning algorithms are defined in this document. An assessment index system and corresponding assessment process are specified in this document. | |
| language | English | |
| title | IEEE Recommended Practice for Framework and Process for Deep Learning Evaluation | en |
| title | IEEE Std 2841-2022 | num |
| type | Standard | |
| page | 32 | |
| tree | IEEE - The Institute of Electrical and Electronics Engineers, Inc.:;2023 | |
| contenttype | Fulltext | |
| subject keywords | IEEE 2841 | |
| subject keywords | algorithm reliability | |
| subject keywords | deep learning evaluation | |
| subject keywords | quality of deep learning algorithm | |
| identifier DOI | 10.1109/IEEESTD.2023.10097701 |