{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:TL5WDOM6JJGS4QUZ6ADSE4OJVY","short_pith_number":"pith:TL5WDOM6","canonical_record":{"source":{"id":"1511.05635","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-18T01:19:00Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"6dd89ad647ffd54e3906fdede068cdcd6a096fcb36e92b9316bf7d6f9158cf3d","abstract_canon_sha256":"09fa8cd0c685d9b74a89f446a34c98dbee88bdc82191cf36a0fef621979927c9"},"schema_version":"1.0"},"canonical_sha256":"9afb61b99e4a4d2e4299f0072271c9ae1392bd1cc05ca83af4bf612b5d4419cc","source":{"kind":"arxiv","id":"1511.05635","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.05635","created_at":"2026-05-18T00:03:26Z"},{"alias_kind":"arxiv_version","alias_value":"1511.05635v1","created_at":"2026-05-18T00:03:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.05635","created_at":"2026-05-18T00:03:26Z"},{"alias_kind":"pith_short_12","alias_value":"TL5WDOM6JJGS","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"TL5WDOM6JJGS4QUZ","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"TL5WDOM6","created_at":"2026-05-18T12:29:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:TL5WDOM6JJGS4QUZ6ADSE4OJVY","target":"record","payload":{"canonical_record":{"source":{"id":"1511.05635","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-18T01:19:00Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"6dd89ad647ffd54e3906fdede068cdcd6a096fcb36e92b9316bf7d6f9158cf3d","abstract_canon_sha256":"09fa8cd0c685d9b74a89f446a34c98dbee88bdc82191cf36a0fef621979927c9"},"schema_version":"1.0"},"canonical_sha256":"9afb61b99e4a4d2e4299f0072271c9ae1392bd1cc05ca83af4bf612b5d4419cc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:26.469148Z","signature_b64":"R3DnkytQolBVD3tXKMvG8CKewhoEBvLEfHfnFcomwHn+GTMXTT1cvxNbtfNcAnXc5bzBU93zNyC18O5QpeDqAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9afb61b99e4a4d2e4299f0072271c9ae1392bd1cc05ca83af4bf612b5d4419cc","last_reissued_at":"2026-05-18T00:03:26.468575Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:26.468575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1511.05635","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":"2026-05-18T00:03:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u6ydMwy9NZmbC930EEXdyQvBf1PcWWhREfuV7WfJR7wDSIb7GR/XHZc5PtxPjde5WAVkfI/PcHTDF6WMzuT8Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T14:44:47.540700Z"},"content_sha256":"2be71f026630c357dd20f584a1999166aeb5ad026b6affc5492f4a642e805884","schema_version":"1.0","event_id":"sha256:2be71f026630c357dd20f584a1999166aeb5ad026b6affc5492f4a642e805884"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:TL5WDOM6JJGS4QUZ6ADSE4OJVY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Competitive Multi-scale Convolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"cs.CV","authors_text":"Gustavo Carneiro, Zhibin Liao","submitted_at":"2015-11-18T01:19:00Z","abstract_excerpt":"In this paper, we introduce a new deep convolutional neural network (ConvNet) module that promotes competition among a set of multi-scale convolutional filters. This new module is inspired by the inception module, where we replace the original collaborative pooling stage (consisting of a concatenation of the multi-scale filter outputs) by a competitive pooling represented by a maxout activation unit. This extension has the following two objectives: 1) the selection of the maximum response among the multi-scale filters prevents filter co-adaptation and allows the formation of multiple sub-netwo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.05635","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":"2026-05-18T00:03:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lrlpnEiJR9gOM85FajBrlyM6iJPVndz0ZvguinZFvU6ReSszenRGokdELcjwTBk5bTWLcwV3K5fxnF7Fvx27Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T14:44:47.541075Z"},"content_sha256":"10e42c439e090c53f16ce5a6cede5bea6a47d7d0438599a2c28e9dde7cd3d544","schema_version":"1.0","event_id":"sha256:10e42c439e090c53f16ce5a6cede5bea6a47d7d0438599a2c28e9dde7cd3d544"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TL5WDOM6JJGS4QUZ6ADSE4OJVY/bundle.json","state_url":"https://pith.science/pith/TL5WDOM6JJGS4QUZ6ADSE4OJVY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TL5WDOM6JJGS4QUZ6ADSE4OJVY/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":"2026-06-01T14:44:47Z","links":{"resolver":"https://pith.science/pith/TL5WDOM6JJGS4QUZ6ADSE4OJVY","bundle":"https://pith.science/pith/TL5WDOM6JJGS4QUZ6ADSE4OJVY/bundle.json","state":"https://pith.science/pith/TL5WDOM6JJGS4QUZ6ADSE4OJVY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TL5WDOM6JJGS4QUZ6ADSE4OJVY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:TL5WDOM6JJGS4QUZ6ADSE4OJVY","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":"09fa8cd0c685d9b74a89f446a34c98dbee88bdc82191cf36a0fef621979927c9","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-18T01:19:00Z","title_canon_sha256":"6dd89ad647ffd54e3906fdede068cdcd6a096fcb36e92b9316bf7d6f9158cf3d"},"schema_version":"1.0","source":{"id":"1511.05635","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.05635","created_at":"2026-05-18T00:03:26Z"},{"alias_kind":"arxiv_version","alias_value":"1511.05635v1","created_at":"2026-05-18T00:03:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.05635","created_at":"2026-05-18T00:03:26Z"},{"alias_kind":"pith_short_12","alias_value":"TL5WDOM6JJGS","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"TL5WDOM6JJGS4QUZ","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"TL5WDOM6","created_at":"2026-05-18T12:29:42Z"}],"graph_snapshots":[{"event_id":"sha256:10e42c439e090c53f16ce5a6cede5bea6a47d7d0438599a2c28e9dde7cd3d544","target":"graph","created_at":"2026-05-18T00:03:26Z","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 new deep convolutional neural network (ConvNet) module that promotes competition among a set of multi-scale convolutional filters. This new module is inspired by the inception module, where we replace the original collaborative pooling stage (consisting of a concatenation of the multi-scale filter outputs) by a competitive pooling represented by a maxout activation unit. This extension has the following two objectives: 1) the selection of the maximum response among the multi-scale filters prevents filter co-adaptation and allows the formation of multiple sub-netwo","authors_text":"Gustavo Carneiro, Zhibin Liao","cross_cats":["cs.LG","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-18T01:19:00Z","title":"Competitive Multi-scale Convolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.05635","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":"sha256:2be71f026630c357dd20f584a1999166aeb5ad026b6affc5492f4a642e805884","target":"record","created_at":"2026-05-18T00:03:26Z","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":"09fa8cd0c685d9b74a89f446a34c98dbee88bdc82191cf36a0fef621979927c9","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-18T01:19:00Z","title_canon_sha256":"6dd89ad647ffd54e3906fdede068cdcd6a096fcb36e92b9316bf7d6f9158cf3d"},"schema_version":"1.0","source":{"id":"1511.05635","kind":"arxiv","version":1}},"canonical_sha256":"9afb61b99e4a4d2e4299f0072271c9ae1392bd1cc05ca83af4bf612b5d4419cc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9afb61b99e4a4d2e4299f0072271c9ae1392bd1cc05ca83af4bf612b5d4419cc","first_computed_at":"2026-05-18T00:03:26.468575Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:03:26.468575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R3DnkytQolBVD3tXKMvG8CKewhoEBvLEfHfnFcomwHn+GTMXTT1cvxNbtfNcAnXc5bzBU93zNyC18O5QpeDqAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:03:26.469148Z","signed_message":"canonical_sha256_bytes"},"source_id":"1511.05635","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2be71f026630c357dd20f584a1999166aeb5ad026b6affc5492f4a642e805884","sha256:10e42c439e090c53f16ce5a6cede5bea6a47d7d0438599a2c28e9dde7cd3d544"],"state_sha256":"d58b642ef47dfbb98e24333f3a7d12bb54543cb083fec943ba663e986c19470b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hZMhx435LtaFqVB0yNKWfZ5imTwR+nS4X6T2jZZAjCDTQ2WzOQMBk5mNT8entg3SQnSCWxI+mL2R/PdRV4W0Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T14:44:47.543131Z","bundle_sha256":"faca55ae0cf7e14ac9637e11021957b4c171f1957c5140303274a90dfe43b2c2"}}