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An automated approach for improving the inference latency and energy efficiency of pretrained CNNs by removing irrelevant pixels with focused convolutions., , , , , , , , , and . CoRR, (2023)PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages., , , , , , , and . MSR, page 57-61. IEEE, (2023)PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software., , , , , , , , and . CoRR, (2024)An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry., , , , , , , and . ICSE, page 2463-2475. IEEE, (2023)PeaTMOSS: Mining Pre-Trained Models in Open-Source Software., , , , , , , , and . CoRR, (2023)Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision., , , , , , and . CoRR, (2023)Reusing Deep Learning Models: Challenges and Directions in Software Engineering., , , , , and . JVA, page 17-30. IEEE, (2023)An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain., , , , , , , and . SCORED@CCS, page 105-114. ACM, (2022)Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics., , , , , , , , , and 4 other author(s). ASE, page 167:1-167:4. ACM, (2022)