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\field{sortinithash}{4d103a86280481745c9c897c925753c0} \field{labelnamesource}{author} \field{labeltitlesource}{title} \field{month}{12} \field{title}{Standard ECMA-404 The JSON Data Interchange Syntax} \field{year}{2017} \true{nocite} \verb{doi} \verb 10.13140/RG.2.2.28181.14560 \endverb \endentry \entry{goodfellow2015explaining}{misc}{} \name{author}{3}{}{% {{hash=d4f74ef4c79f3bb1e51e378184d8850e}{% family={Goodfellow}, familyi={G\bibinitperiod}, given={Ian\bibnamedelima J.}, giveni={I\bibinitperiod\bibinitdelim J\bibinitperiod}}}% {{hash=8f128e70084608a2c29c497ebd794f87}{% family={Shlens}, familyi={S\bibinitperiod}, given={Jonathon}, giveni={J\bibinitperiod}}}% {{hash=ed568d9c3bb059e6bf22899fbf170f86}{% family={Szegedy}, familyi={S\bibinitperiod}, given={Christian}, giveni={C\bibinitperiod}}}% } \strng{namehash}{07b2928cf9addb6cf2d09332e9d7ce18} \strng{fullhash}{07b2928cf9addb6cf2d09332e9d7ce18} \strng{bibnamehash}{07b2928cf9addb6cf2d09332e9d7ce18} \strng{authorbibnamehash}{07b2928cf9addb6cf2d09332e9d7ce18} \strng{authornamehash}{07b2928cf9addb6cf2d09332e9d7ce18} \strng{authorfullhash}{07b2928cf9addb6cf2d09332e9d7ce18} \field{sortinit}{G} \field{sortinithash}{32d67eca0634bf53703493fb1090a2e8} \field{labelnamesource}{author} \field{labeltitlesource}{title} \field{eprintclass}{stat.ML} \field{journaltitle}{arXiv} \field{title}{Explaining and Harnessing Adversarial Examples} \field{volume}{1412.6572} \field{year}{2015} \true{nocite} \endentry \entry{ieee3129}{article}{} \field{sortinit}{I} \field{sortinithash}{8d291c51ee89b6cd86bf5379f0b151d8} \field{labeltitlesource}{title} \field{journaltitle}{IEEE Std 3129-2023} \field{title}{IEEE Standard for Robustness Testing and Evaluation of Artificial Intelligence (AI)-based Image Recognition Service} \field{year}{2023} \true{nocite} \field{pages}{1\bibrangedash 34} \range{pages}{34} \verb{doi} \verb 10.1109/IEEESTD.2023.10141539 \endverb \keyw{IEEE Standards;Robustness;Image recording;Testing;Artificial intelligence;Performance evaluation;adversarial attacks;artificial Intelligence-based services;assessment framework;common corruption;IEEE 3129;robustness} \endentry \entry{schapire1989strength}{inproceedings}{} \name{author}{1}{}{% {{hash=bd36be65806a94f14599091fa7ddc7d3}{% family={Schapire}, familyi={S\bibinitperiod}, given={R.E.}, giveni={R\bibinitperiod}}}% } \strng{namehash}{bd36be65806a94f14599091fa7ddc7d3} \strng{fullhash}{bd36be65806a94f14599091fa7ddc7d3} \strng{bibnamehash}{bd36be65806a94f14599091fa7ddc7d3} \strng{authorbibnamehash}{bd36be65806a94f14599091fa7ddc7d3} \strng{authornamehash}{bd36be65806a94f14599091fa7ddc7d3} \strng{authorfullhash}{bd36be65806a94f14599091fa7ddc7d3} \field{sortinit}{S} \field{sortinithash}{b164b07b29984b41daf1e85279fbc5ab} \field{labelnamesource}{author} \field{labeltitlesource}{title} \field{booktitle}{30th Annual Symposium on Foundations of Computer Science} \field{title}{The strength of weak learnability} \field{year}{1989} \true{nocite} \field{pages}{28\bibrangedash 33} \range{pages}{6} \verb{doi} \verb 10.1109/SFCS.1989.63451 \endverb \keyw{Polynomials;Boosting;Laboratories;Computer science;Upper bound;Boolean functions;Filtering} \endentry \entry{simonyan2014very}{article}{} \name{author}{2}{}{% {{hash=9d16b7284df92c9adaee86c37ab992df}{% family={Simonyan}, familyi={S\bibinitperiod}, given={Karen}, giveni={K\bibinitperiod}}}% {{hash=c72fc39e94030f67717052309266a44d}{% family={Zisserman}, familyi={Z\bibinitperiod}, given={Andrew}, giveni={A\bibinitperiod}}}% } \strng{namehash}{25d2f3c4577a6632d37f0126cc781232} \strng{fullhash}{25d2f3c4577a6632d37f0126cc781232} \strng{bibnamehash}{25d2f3c4577a6632d37f0126cc781232} \strng{authorbibnamehash}{25d2f3c4577a6632d37f0126cc781232} \strng{authornamehash}{25d2f3c4577a6632d37f0126cc781232} \strng{authorfullhash}{25d2f3c4577a6632d37f0126cc781232} \field{sortinit}{S} \field{sortinithash}{b164b07b29984b41daf1e85279fbc5ab} \field{labelnamesource}{author} \field{labeltitlesource}{title} \field{journaltitle}{arXiv 1409.1556} \field{month}{09} \field{title}{Very Deep Convolutional Networks for Large-Scale Image Recognition} \field{year}{2014} \true{nocite} \endentry \entry{szegedy2014intriguing}{misc}{} \name{author}{7}{}{% {{hash=ed568d9c3bb059e6bf22899fbf170f86}{% family={Szegedy}, familyi={S\bibinitperiod}, given={Christian}, giveni={C\bibinitperiod}}}% {{hash=e9fec85bbce1b087a6ebefe26e73f7bf}{% family={Zaremba}, familyi={Z\bibinitperiod}, given={Wojciech}, giveni={W\bibinitperiod}}}% {{hash=8d569d1d5b8b5a7836017a98b430f959}{% family={Sutskever}, familyi={S\bibinitperiod}, given={Ilya}, giveni={I\bibinitperiod}}}% {{hash=c83b564e32475f10dcc91be7e66d3e81}{% family={Bruna}, familyi={B\bibinitperiod}, given={Joan}, giveni={J\bibinitperiod}}}% {{hash=8bbc4c5d96f205bada839e74e0202146}{% family={Erhan}, familyi={E\bibinitperiod}, given={Dumitru}, giveni={D\bibinitperiod}}}% 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\field{eprintclass}{cs.CV} \field{journaltitle}{arXiv} \field{title}{Deep Layer Aggregation} \field{year}{2019} \true{nocite} \verb{eprint} \verb 1707.06484 \endverb \endentry \enddatalist \endrefsection \endinput