{"id":126666,"date":"2024-10-19T05:39:25","date_gmt":"2024-10-19T05:39:25","guid":{"rendered":"https:\/\/pdfstandards.shop\/product\/uncategorized\/bs-iso-iec-24029-22023-2024\/"},"modified":"2024-10-24T23:21:31","modified_gmt":"2024-10-24T23:21:31","slug":"bs-iso-iec-24029-22023-2024","status":"publish","type":"product","link":"https:\/\/pdfstandards.shop\/product\/publishers\/bsi\/bs-iso-iec-24029-22023-2024\/","title":{"rendered":"BS ISO\/IEC 24029-2:2023 2024"},"content":{"rendered":"

PDF Catalog<\/h4>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
PDF Pages<\/th>\nPDF Title<\/th>\n<\/tr>\n
2<\/td>\nundefined <\/td>\n<\/tr>\n
6<\/td>\nForeword <\/td>\n<\/tr>\n
7<\/td>\nIntroduction <\/td>\n<\/tr>\n
9<\/td>\n1 Scope
2 Normative references
3 Terms and definitions <\/td>\n<\/tr>\n
12<\/td>\n4 Abbreviated terms
5 Robustness assessment
5.1 General <\/td>\n<\/tr>\n
13<\/td>\n5.2 Notion of domain <\/td>\n<\/tr>\n
14<\/td>\n5.3 Stability
5.3.1 Stability property
5.3.2 Stability criterion
5.4 Sensitivity
5.4.1 Sensitivity property <\/td>\n<\/tr>\n
15<\/td>\n5.4.2 Sensitivity criterion
5.5 Relevance
5.5.1 Relevance property
5.5.2 Relevance criterion <\/td>\n<\/tr>\n
16<\/td>\n5.6 Reachability
5.6.1 Reachability property
5.6.2 Reachability criterion <\/td>\n<\/tr>\n
17<\/td>\n6 Applicability of formal methods on neural networks
6.1 Types of neural network concerned
6.1.1 Architectures of neural networks <\/td>\n<\/tr>\n
18<\/td>\n6.1.2 Neural networks input data type <\/td>\n<\/tr>\n
20<\/td>\n6.2 Types of formal methods applicable
6.2.1 General <\/td>\n<\/tr>\n
21<\/td>\n6.2.2 Solver
6.2.3 Abstract interpretation
6.2.4 Reachability analysis in deterministic environments <\/td>\n<\/tr>\n
22<\/td>\n6.2.5 Reachability analysis in non-deterministic environments
6.2.6 Model checking
6.3 Summary <\/td>\n<\/tr>\n
23<\/td>\n7 Robustness during the life cycle
7.1 General
7.2 During design and development
7.2.1 General
7.2.2 Identifying the recognized features <\/td>\n<\/tr>\n
24<\/td>\n7.2.3 Checking separability
7.3 During verification and validation
7.3.1 General <\/td>\n<\/tr>\n
25<\/td>\n7.3.2 Covering parts of the input domain
7.3.3 Measuring perturbation impact <\/td>\n<\/tr>\n
26<\/td>\n7.4 During deployment <\/td>\n<\/tr>\n
27<\/td>\n7.5 During operation and monitoring
7.5.1 General
7.5.2 Robustness on a domain of operation <\/td>\n<\/tr>\n
28<\/td>\n7.5.3 Changes in robustness <\/td>\n<\/tr>\n
29<\/td>\nBibliography <\/td>\n<\/tr>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Artificial intelligence (AI). Assessment of the robustness of neural networks – Methodology for the use of formal methods<\/b><\/p>\n\n\n\n\n
Published By<\/td>\nPublication Date<\/td>\nNumber of Pages<\/td>\n<\/tr>\n
BSI<\/b><\/a><\/td>\n2024<\/td>\n32<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"featured_media":126668,"template":"","meta":{"rank_math_lock_modified_date":false,"ep_exclude_from_search":false},"product_cat":[2641],"product_tag":[],"class_list":{"0":"post-126666","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-bsi","8":"first","9":"instock","10":"sold-individually","11":"shipping-taxable","12":"purchasable","13":"product-type-simple"},"_links":{"self":[{"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/product\/126666","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/types\/product"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/media\/126668"}],"wp:attachment":[{"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/media?parent=126666"}],"wp:term":[{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/product_cat?post=126666"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/product_tag?post=126666"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}