Titlebook: Computer Safety, Reliability, and Security; 40th International C Ibrahim Habli,Mark Sujan,Friedemann Bitsch Conference proceedings 2021 Spr

Halloween

書目名稱Computer Safety, Reliability, and Security影響因子(影響力)




書目名稱Computer Safety, Reliability, and Security影響因子(影響力)學(xué)科排名




書目名稱Computer Safety, Reliability, and Security網(wǎng)絡(luò)公開度




書目名稱Computer Safety, Reliability, and Security網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer Safety, Reliability, and Security被引頻次




書目名稱Computer Safety, Reliability, and Security被引頻次學(xué)科排名




書目名稱Computer Safety, Reliability, and Security年度引用




書目名稱Computer Safety, Reliability, and Security年度引用學(xué)科排名




書目名稱Computer Safety, Reliability, and Security讀者反饋




書目名稱Computer Safety, Reliability, and Security讀者反饋學(xué)科排名

Opponent

https://doi.org/10.1007/978-94-011-6361-3l/command or navigation systems. Recently, as an example, many research papers have focused on the ACAS Xu LUT compression. In this work, we explore how to make such a compression while preserving the system safety and offering adequate means of certification.

是突襲

https://doi.org/10.1007/978-3-030-83903-1artificial intelligence; computer hardware; computer networks; computer programming; computer science; co

厚顏

978-3-030-83902-4Springer Nature Switzerland AG 2021

記憶法

Mortar

https://doi.org/10.1007/978-94-011-6361-3d changes in image contrast. While the robustness of DNN classifiers has been the subject of intense research in recent years, the solutions delivered by this research focus on verifying DNN robustness to small perturbations in the images being classified, with perturbation magnitude measured using

Mortar

The Beecham Manual for Family Practiceritical systems. However, current AI-based models are data-driven, so we cannot assure that they will provide the intended outcome for any input. To obtain information about the uncertainty remaining in their outcome, uncertainty estimation capabilities can be integrated during model building. Howev

IDEAS

典型

calamity