{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:HFSFI4G6NM3EGCVIXSH5PG52W5","short_pith_number":"pith:HFSFI4G6","canonical_record":{"source":{"id":"1711.04237","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-12T05:11:42Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"83e788b9c8c32ca3d324f21d9e9da8d5336d7bd878c21627a6524caf6b124a08","abstract_canon_sha256":"f41e97f0e799c4e99acfd7018f276872a79dc3479e018812435000fb3efdd748"},"schema_version":"1.0"},"canonical_sha256":"39645470de6b36430aa8bc8fd79bbab750ddf1cd4fddc020e79c9ee7a4784991","source":{"kind":"arxiv","id":"1711.04237","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.04237","created_at":"2026-05-18T00:21:04Z"},{"alias_kind":"arxiv_version","alias_value":"1711.04237v3","created_at":"2026-05-18T00:21:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.04237","created_at":"2026-05-18T00:21:04Z"},{"alias_kind":"pith_short_12","alias_value":"HFSFI4G6NM3E","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HFSFI4G6NM3EGCVI","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HFSFI4G6","created_at":"2026-05-18T12:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:HFSFI4G6NM3EGCVIXSH5PG52W5","target":"record","payload":{"canonical_record":{"source":{"id":"1711.04237","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-12T05:11:42Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"83e788b9c8c32ca3d324f21d9e9da8d5336d7bd878c21627a6524caf6b124a08","abstract_canon_sha256":"f41e97f0e799c4e99acfd7018f276872a79dc3479e018812435000fb3efdd748"},"schema_version":"1.0"},"canonical_sha256":"39645470de6b36430aa8bc8fd79bbab750ddf1cd4fddc020e79c9ee7a4784991","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:21:04.513311Z","signature_b64":"4iAkwO9bPJvN64W3idKEMHxcle3Qdns/orsQwvrCXd2lQ8DYzvjXjNaDpwBD6+RHYWXYihpdgV6PpEFF80pECg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"39645470de6b36430aa8bc8fd79bbab750ddf1cd4fddc020e79c9ee7a4784991","last_reissued_at":"2026-05-18T00:21:04.512733Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:21:04.512733Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.04237","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:21:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vUJGujlSXIClJjMb86qfFEcz5/YcXyQPTgOBcPr5hPP777XByuRxleIarxwNCWAvE5tRwfDXW74l2vlpMRklDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T20:12:23.141651Z"},"content_sha256":"5c42277a0c8fc0d657a1f3c9419aa513606ed84aea68ba29f2bd2b8989a08b6b","schema_version":"1.0","event_id":"sha256:5c42277a0c8fc0d657a1f3c9419aa513606ed84aea68ba29f2bd2b8989a08b6b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:HFSFI4G6NM3EGCVIXSH5PG52W5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"D-PCN: Parallel Convolutional Networks for Image Recognition via a Discriminator","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Gang Peng, Shiqi Yang","submitted_at":"2017-11-12T05:11:42Z","abstract_excerpt":"In this paper, we introduce a simple but quite effective recognition framework dubbed D-PCN, aiming at enhancing feature extracting ability of CNN. The framework consists of two parallel CNNs, a discriminator and an extra classifier which takes integrated features from parallel networks and gives final prediction. The discriminator is core which drives parallel networks to focus on different regions and learn complementary representations. The corresponding joint training strategy is introduced which ensures the utilization of discriminator. We validate D-PCN with several CNN models on two ben"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.04237","kind":"arxiv","version":3},"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":"2026-05-18T00:21:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F8H+juo67avm69pkj/zAlh7GUnkskrRFn/b0YuvLKEC4r4U7m/7Ai8uXkPL+3jQQfYlAtDajGBTIo1W+MmIABw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T20:12:23.141995Z"},"content_sha256":"850b6bcad8321c8b574f64775d20c8bdae1e65a8c8d112cfc5ed28754215c768","schema_version":"1.0","event_id":"sha256:850b6bcad8321c8b574f64775d20c8bdae1e65a8c8d112cfc5ed28754215c768"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HFSFI4G6NM3EGCVIXSH5PG52W5/bundle.json","state_url":"https://pith.science/pith/HFSFI4G6NM3EGCVIXSH5PG52W5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HFSFI4G6NM3EGCVIXSH5PG52W5/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":"2026-05-27T20:12:23Z","links":{"resolver":"https://pith.science/pith/HFSFI4G6NM3EGCVIXSH5PG52W5","bundle":"https://pith.science/pith/HFSFI4G6NM3EGCVIXSH5PG52W5/bundle.json","state":"https://pith.science/pith/HFSFI4G6NM3EGCVIXSH5PG52W5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HFSFI4G6NM3EGCVIXSH5PG52W5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:HFSFI4G6NM3EGCVIXSH5PG52W5","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":"f41e97f0e799c4e99acfd7018f276872a79dc3479e018812435000fb3efdd748","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-12T05:11:42Z","title_canon_sha256":"83e788b9c8c32ca3d324f21d9e9da8d5336d7bd878c21627a6524caf6b124a08"},"schema_version":"1.0","source":{"id":"1711.04237","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.04237","created_at":"2026-05-18T00:21:04Z"},{"alias_kind":"arxiv_version","alias_value":"1711.04237v3","created_at":"2026-05-18T00:21:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.04237","created_at":"2026-05-18T00:21:04Z"},{"alias_kind":"pith_short_12","alias_value":"HFSFI4G6NM3E","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HFSFI4G6NM3EGCVI","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HFSFI4G6","created_at":"2026-05-18T12:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:850b6bcad8321c8b574f64775d20c8bdae1e65a8c8d112cfc5ed28754215c768","target":"graph","created_at":"2026-05-18T00:21:04Z","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 this paper, we introduce a simple but quite effective recognition framework dubbed D-PCN, aiming at enhancing feature extracting ability of CNN. The framework consists of two parallel CNNs, a discriminator and an extra classifier which takes integrated features from parallel networks and gives final prediction. The discriminator is core which drives parallel networks to focus on different regions and learn complementary representations. The corresponding joint training strategy is introduced which ensures the utilization of discriminator. We validate D-PCN with several CNN models on two ben","authors_text":"Gang Peng, Shiqi Yang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-12T05:11:42Z","title":"D-PCN: Parallel Convolutional Networks for Image Recognition via a Discriminator"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.04237","kind":"arxiv","version":3},"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":"sha256:5c42277a0c8fc0d657a1f3c9419aa513606ed84aea68ba29f2bd2b8989a08b6b","target":"record","created_at":"2026-05-18T00:21:04Z","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":"f41e97f0e799c4e99acfd7018f276872a79dc3479e018812435000fb3efdd748","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-12T05:11:42Z","title_canon_sha256":"83e788b9c8c32ca3d324f21d9e9da8d5336d7bd878c21627a6524caf6b124a08"},"schema_version":"1.0","source":{"id":"1711.04237","kind":"arxiv","version":3}},"canonical_sha256":"39645470de6b36430aa8bc8fd79bbab750ddf1cd4fddc020e79c9ee7a4784991","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"39645470de6b36430aa8bc8fd79bbab750ddf1cd4fddc020e79c9ee7a4784991","first_computed_at":"2026-05-18T00:21:04.512733Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:21:04.512733Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4iAkwO9bPJvN64W3idKEMHxcle3Qdns/orsQwvrCXd2lQ8DYzvjXjNaDpwBD6+RHYWXYihpdgV6PpEFF80pECg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:21:04.513311Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.04237","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5c42277a0c8fc0d657a1f3c9419aa513606ed84aea68ba29f2bd2b8989a08b6b","sha256:850b6bcad8321c8b574f64775d20c8bdae1e65a8c8d112cfc5ed28754215c768"],"state_sha256":"504b27f3a0dd9e4a718c44bcfad470e07beedb6d2e2d46e76bf86db058dfc309"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ti6UTXgrzt60Et0BjCnB842YbMmSEm7aR6UOX/MtnFnRy8dpA47w2K/bxe7sYaUr12vKeH6eaZFhq/5I2EItCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T20:12:23.144115Z","bundle_sha256":"2c5f8274ec4a70ecd94dd665d8952c4f57513c61e133d94dbf4df221539645f3"}}