{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:LZEXHHF5RENZZ6H75DA2WKGGA4","short_pith_number":"pith:LZEXHHF5","canonical_record":{"source":{"id":"1809.06582","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-18T08:25:01Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"2fca5d6167edc27db89ad0254f9966408e5292b0ac5ff2fc000f572740a442cc","abstract_canon_sha256":"0995b31cbbe43be368755c966cd62ca59ce04d746c67a03564ef56019547bb18"},"schema_version":"1.0"},"canonical_sha256":"5e49739cbd891b9cf8ffe8c1ab28c6072d5b71c347b284265f60e21c406f6557","source":{"kind":"arxiv","id":"1809.06582","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06582","created_at":"2026-05-17T23:58:30Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06582v2","created_at":"2026-05-17T23:58:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06582","created_at":"2026-05-17T23:58:30Z"},{"alias_kind":"pith_short_12","alias_value":"LZEXHHF5RENZ","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"LZEXHHF5RENZZ6H7","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"LZEXHHF5","created_at":"2026-05-18T12:32:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:LZEXHHF5RENZZ6H75DA2WKGGA4","target":"record","payload":{"canonical_record":{"source":{"id":"1809.06582","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-18T08:25:01Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"2fca5d6167edc27db89ad0254f9966408e5292b0ac5ff2fc000f572740a442cc","abstract_canon_sha256":"0995b31cbbe43be368755c966cd62ca59ce04d746c67a03564ef56019547bb18"},"schema_version":"1.0"},"canonical_sha256":"5e49739cbd891b9cf8ffe8c1ab28c6072d5b71c347b284265f60e21c406f6557","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:58:30.499535Z","signature_b64":"5oAK0mFQZeeHrYU3IzqJlsxR9EPemEelXErwKw8yAS+14og6Vyq//2hp1NQsU4m74axVhUDKrlnz0QzrAVfbDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5e49739cbd891b9cf8ffe8c1ab28c6072d5b71c347b284265f60e21c406f6557","last_reissued_at":"2026-05-17T23:58:30.499040Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:58:30.499040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.06582","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:58:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UoJ0oMyP6jyMVZzrhuM+CQ5LDxKhbxbC9LVQGCtVlkXgTHqTbZCcLZqp/zIF3Fm+5xbD3dCZs6D1la5nN8HxCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T07:26:06.101061Z"},"content_sha256":"0b376037dc09c0b500a062e2cf733e353b8b2b4ae2677e101f76ca865e6fbee7","schema_version":"1.0","event_id":"sha256:0b376037dc09c0b500a062e2cf733e353b8b2b4ae2677e101f76ca865e6fbee7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:LZEXHHF5RENZZ6H75DA2WKGGA4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Symbolic Tensor Neural Networks for Digital Media - from Tensor Processing via BNF Graph Rules to CREAMS Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"Wladyslaw Skarbek","submitted_at":"2018-09-18T08:25:01Z","abstract_excerpt":"This tutorial material on Convolutional Neural Networks (CNN) and its applications in digital media research is based on the concept of Symbolic Tensor Neural Networks. The set of STNN expressions is specified in Backus-Naur Form (BNF) which is annotated by constraints typical for labeled acyclic directed graphs (DAG). The BNF induction begins from a collection of neural unit symbols with extra (up to five) decoration fields (including tensor depth and sharing fields). The inductive rules provide not only the general graph structure but also the specific shortcuts for residual blocks of units."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06582","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:58:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bCGIpbHIMcrBl6OhERCBcGVsrhCT1sRp+342Z+vdWK5DkTfKgtMQ1OQOPhfo5N+oqNwfJfu3Ou/svOV8aB2LAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T07:26:06.101420Z"},"content_sha256":"05bf2e18d2b2c7dc16ec569d3e7ca5e01997700dc0cf09a2bb18417491b9da8c","schema_version":"1.0","event_id":"sha256:05bf2e18d2b2c7dc16ec569d3e7ca5e01997700dc0cf09a2bb18417491b9da8c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LZEXHHF5RENZZ6H75DA2WKGGA4/bundle.json","state_url":"https://pith.science/pith/LZEXHHF5RENZZ6H75DA2WKGGA4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LZEXHHF5RENZZ6H75DA2WKGGA4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-30T07:26:06Z","links":{"resolver":"https://pith.science/pith/LZEXHHF5RENZZ6H75DA2WKGGA4","bundle":"https://pith.science/pith/LZEXHHF5RENZZ6H75DA2WKGGA4/bundle.json","state":"https://pith.science/pith/LZEXHHF5RENZZ6H75DA2WKGGA4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LZEXHHF5RENZZ6H75DA2WKGGA4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:LZEXHHF5RENZZ6H75DA2WKGGA4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0995b31cbbe43be368755c966cd62ca59ce04d746c67a03564ef56019547bb18","cross_cats_sorted":["cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-18T08:25:01Z","title_canon_sha256":"2fca5d6167edc27db89ad0254f9966408e5292b0ac5ff2fc000f572740a442cc"},"schema_version":"1.0","source":{"id":"1809.06582","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06582","created_at":"2026-05-17T23:58:30Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06582v2","created_at":"2026-05-17T23:58:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06582","created_at":"2026-05-17T23:58:30Z"},{"alias_kind":"pith_short_12","alias_value":"LZEXHHF5RENZ","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"LZEXHHF5RENZZ6H7","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"LZEXHHF5","created_at":"2026-05-18T12:32:37Z"}],"graph_snapshots":[{"event_id":"sha256:05bf2e18d2b2c7dc16ec569d3e7ca5e01997700dc0cf09a2bb18417491b9da8c","target":"graph","created_at":"2026-05-17T23:58:30Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"This tutorial material on Convolutional Neural Networks (CNN) and its applications in digital media research is based on the concept of Symbolic Tensor Neural Networks. The set of STNN expressions is specified in Backus-Naur Form (BNF) which is annotated by constraints typical for labeled acyclic directed graphs (DAG). The BNF induction begins from a collection of neural unit symbols with extra (up to five) decoration fields (including tensor depth and sharing fields). The inductive rules provide not only the general graph structure but also the specific shortcuts for residual blocks of units.","authors_text":"Wladyslaw Skarbek","cross_cats":["cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-18T08:25:01Z","title":"Symbolic Tensor Neural Networks for Digital Media - from Tensor Processing via BNF Graph Rules to CREAMS Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06582","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0b376037dc09c0b500a062e2cf733e353b8b2b4ae2677e101f76ca865e6fbee7","target":"record","created_at":"2026-05-17T23:58:30Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0995b31cbbe43be368755c966cd62ca59ce04d746c67a03564ef56019547bb18","cross_cats_sorted":["cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-18T08:25:01Z","title_canon_sha256":"2fca5d6167edc27db89ad0254f9966408e5292b0ac5ff2fc000f572740a442cc"},"schema_version":"1.0","source":{"id":"1809.06582","kind":"arxiv","version":2}},"canonical_sha256":"5e49739cbd891b9cf8ffe8c1ab28c6072d5b71c347b284265f60e21c406f6557","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5e49739cbd891b9cf8ffe8c1ab28c6072d5b71c347b284265f60e21c406f6557","first_computed_at":"2026-05-17T23:58:30.499040Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:58:30.499040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5oAK0mFQZeeHrYU3IzqJlsxR9EPemEelXErwKw8yAS+14og6Vyq//2hp1NQsU4m74axVhUDKrlnz0QzrAVfbDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:58:30.499535Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.06582","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0b376037dc09c0b500a062e2cf733e353b8b2b4ae2677e101f76ca865e6fbee7","sha256:05bf2e18d2b2c7dc16ec569d3e7ca5e01997700dc0cf09a2bb18417491b9da8c"],"state_sha256":"70f5045ae8b053d2fa30d7197420c4f123d2155b3238b2c838eeff35af75fd71"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jn6D2qfUv5AAg4rjGWjkBq7pc2vKMrzLCZV50ISzF2USHJHBxP3kDmXSMBu2yEDzdqLhmTPCeD1K5ofZUq0mCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T07:26:06.103467Z","bundle_sha256":"5ca222d326d3baaa866d82e2aeb419d122b379bd7650f74f03b53b52cf8998f7"}}