{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:IP7INKYE6CHW7AW5FYB3PAZYV4","short_pith_number":"pith:IP7INKYE","canonical_record":{"source":{"id":"1809.09645","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-25T18:23:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"eec3a6ef5094522a03143e8b0b9e4238b47e0e3fbbf514d0c8089cf1bd448050","abstract_canon_sha256":"39cc709bc5d96e737010a553d515fc60f8bb3d22cdb4713815c83b20ba3d3a91"},"schema_version":"1.0"},"canonical_sha256":"43fe86ab04f08f6f82dd2e03b78338af35e941ff9c58ea12b329fa64db88046a","source":{"kind":"arxiv","id":"1809.09645","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.09645","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"1809.09645v1","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.09645","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"IP7INKYE6CHW","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"IP7INKYE6CHW7AW5","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"IP7INKYE","created_at":"2026-05-18T12:32:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:IP7INKYE6CHW7AW5FYB3PAZYV4","target":"record","payload":{"canonical_record":{"source":{"id":"1809.09645","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-25T18:23:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"eec3a6ef5094522a03143e8b0b9e4238b47e0e3fbbf514d0c8089cf1bd448050","abstract_canon_sha256":"39cc709bc5d96e737010a553d515fc60f8bb3d22cdb4713815c83b20ba3d3a91"},"schema_version":"1.0"},"canonical_sha256":"43fe86ab04f08f6f82dd2e03b78338af35e941ff9c58ea12b329fa64db88046a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:44.153733Z","signature_b64":"Wvjb3NDyA6tjEizwKludo8ZEp7oqKohJpD+uEUZyyoprSVGaO0FYzNYn5/Lc0x/ugyBbgRlwG7co2eIeQed7CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"43fe86ab04f08f6f82dd2e03b78338af35e941ff9c58ea12b329fa64db88046a","last_reissued_at":"2026-05-18T00:04:44.152933Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:44.152933Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.09645","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:04:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"II6/nV5Qo/NXOOzMnBr81HJjgyTqTBtNBa5hQyYmuU4KGiCSkw9SIeoBVEe4NPxHiieeLSs4oZNcGwPh7CbUDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T16:28:59.262225Z"},"content_sha256":"6e64247d141109ec49a736aabb1f422ac99fc3a9769ff1d677851ce98c72672e","schema_version":"1.0","event_id":"sha256:6e64247d141109ec49a736aabb1f422ac99fc3a9769ff1d677851ce98c72672e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:IP7INKYE6CHW7AW5FYB3PAZYV4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Neural Networks for Pattern Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Alexander Huyen, Kyongsik Yun, Thomas Lu","submitted_at":"2018-09-25T18:23:49Z","abstract_excerpt":"In the field of pattern recognition research, the method of using deep neural networks based on improved computing hardware recently attracted attention because of their superior accuracy compared to conventional methods. Deep neural networks simulate the human visual system and achieve human equivalent accuracy in image classification, object detection, and segmentation. This chapter introduces the basic structure of deep neural networks that simulate human neural networks. Then we identify the operational processes and applications of conditional generative adversarial networks, which are be"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.09645","kind":"arxiv","version":1},"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":"2026-05-18T00:04:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BW3U/TjG7FjRYKYGzJh53uJCEXwYKAgdAT+72Uwdf5l3na6jK0BmRL23cz+yWTdXesvF28rZvpAnHL0b2G84BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T16:28:59.262900Z"},"content_sha256":"a000b7533fe307add580cf11b3250c38ba9a02271c1dddbfeaa5bf7cc8447f80","schema_version":"1.0","event_id":"sha256:a000b7533fe307add580cf11b3250c38ba9a02271c1dddbfeaa5bf7cc8447f80"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IP7INKYE6CHW7AW5FYB3PAZYV4/bundle.json","state_url":"https://pith.science/pith/IP7INKYE6CHW7AW5FYB3PAZYV4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IP7INKYE6CHW7AW5FYB3PAZYV4/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":"2026-08-03T16:28:59Z","links":{"resolver":"https://pith.science/pith/IP7INKYE6CHW7AW5FYB3PAZYV4","bundle":"https://pith.science/pith/IP7INKYE6CHW7AW5FYB3PAZYV4/bundle.json","state":"https://pith.science/pith/IP7INKYE6CHW7AW5FYB3PAZYV4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IP7INKYE6CHW7AW5FYB3PAZYV4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:IP7INKYE6CHW7AW5FYB3PAZYV4","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":"39cc709bc5d96e737010a553d515fc60f8bb3d22cdb4713815c83b20ba3d3a91","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-25T18:23:49Z","title_canon_sha256":"eec3a6ef5094522a03143e8b0b9e4238b47e0e3fbbf514d0c8089cf1bd448050"},"schema_version":"1.0","source":{"id":"1809.09645","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.09645","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"1809.09645v1","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.09645","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"IP7INKYE6CHW","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"IP7INKYE6CHW7AW5","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"IP7INKYE","created_at":"2026-05-18T12:32:31Z"}],"graph_snapshots":[{"event_id":"sha256:a000b7533fe307add580cf11b3250c38ba9a02271c1dddbfeaa5bf7cc8447f80","target":"graph","created_at":"2026-05-18T00:04:44Z","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":"In the field of pattern recognition research, the method of using deep neural networks based on improved computing hardware recently attracted attention because of their superior accuracy compared to conventional methods. Deep neural networks simulate the human visual system and achieve human equivalent accuracy in image classification, object detection, and segmentation. This chapter introduces the basic structure of deep neural networks that simulate human neural networks. Then we identify the operational processes and applications of conditional generative adversarial networks, which are be","authors_text":"Alexander Huyen, Kyongsik Yun, Thomas Lu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-25T18:23:49Z","title":"Deep Neural Networks for Pattern Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.09645","kind":"arxiv","version":1},"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":"sha256:6e64247d141109ec49a736aabb1f422ac99fc3a9769ff1d677851ce98c72672e","target":"record","created_at":"2026-05-18T00:04:44Z","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":"39cc709bc5d96e737010a553d515fc60f8bb3d22cdb4713815c83b20ba3d3a91","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-25T18:23:49Z","title_canon_sha256":"eec3a6ef5094522a03143e8b0b9e4238b47e0e3fbbf514d0c8089cf1bd448050"},"schema_version":"1.0","source":{"id":"1809.09645","kind":"arxiv","version":1}},"canonical_sha256":"43fe86ab04f08f6f82dd2e03b78338af35e941ff9c58ea12b329fa64db88046a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"43fe86ab04f08f6f82dd2e03b78338af35e941ff9c58ea12b329fa64db88046a","first_computed_at":"2026-05-18T00:04:44.152933Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:04:44.152933Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Wvjb3NDyA6tjEizwKludo8ZEp7oqKohJpD+uEUZyyoprSVGaO0FYzNYn5/Lc0x/ugyBbgRlwG7co2eIeQed7CA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:04:44.153733Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.09645","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6e64247d141109ec49a736aabb1f422ac99fc3a9769ff1d677851ce98c72672e","sha256:a000b7533fe307add580cf11b3250c38ba9a02271c1dddbfeaa5bf7cc8447f80"],"state_sha256":"7089acc325a09415ab7c0d70b77533b9d0c18c872e1491f5233d0258b503a105"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VDjd5XluJonXSoqhwrvdILefcS9wAhwrnStcW6bZjKFMVA7vneoplaGRK3TR9dCcE2/NrR3FxZg2RAXoDorVBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T16:28:59.266144Z","bundle_sha256":"32b20e81ab5af1b9931ff0315f3a939f9d3cfb30b97634de6ab85a2975e6979d"}}