On the Variability of Software Engineering Needs for Deep Learning: Stages, Trends, and Application Types-Reference-Cited by-同舟云学术

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On the Variability of Software Engineering Needs for Deep Learning: Stages, Trends, and Application Types

Published:2023-02-01 Issue:2 Volume:49 Page:760-776
ISSN:0098-5589
Container-title:IEEE Transactions on Software Engineering
language:
Short-container-title:IIEEE Trans. Software Eng.

Author:

Gao Kai¹^ORCID,Wang Zhixing²,Mockus Audris³^ORCID,Zhou Minghui⁴^ORCID

Affiliation:

1. School of Software & Microelectrics, Peking University, Beijing, China

2. School of Information Science and Technology, University of Tokyo, Bunkyo City, Tokyo, Japan

3. Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA

4. School of Computer Science, Peking University, Beijing, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Software

Link

http://xplorestaging.ieee.org/ielx7/32/10044379/09745323.pdf?arnumber=9745323

Reference71 articles.

1. A comprehensive study on challenges in deploying deep learning based software

2. Transfer learning - Wikipedia,0

3. An Empirical Study Towards Characterizing Deep Learning Development and Deployment Across Different Frameworks and Platforms

4. Image segmentation - Wikipedia,0

5. Why is Developing Machine Learning Applications Challenging? A Study on Stack Overflow Posts

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1. PyRadar: Towards Automatically Retrieving and Validating Source Code Repository Information for PyPI Packages;Proceedings of the ACM on Software Engineering;2024-07-12

2. Characterizing Deep Learning Package Supply Chains in PyPI: Domains, Clusters, and Disengagement;ACM Transactions on Software Engineering and Methodology;2024-04-18

3. Sustainability Forecasting for Deep Learning Packages;2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER);2024-03-12

4. AutoML from Software Engineering Perspective: Landscapes and Challenges;2023 IEEE/ACM 20th International Conference on Mining Software Repositories (MSR);2023-05

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