{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:SCY4H53XDBWR2DZXFMXI475W2A","short_pith_number":"pith:SCY4H53X","canonical_record":{"source":{"id":"1709.00516","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-02T01:38:34Z","cross_cats_sorted":[],"title_canon_sha256":"23a466c8003377c54523d8299cd1c62ac61071afda9c2b54e11fab8200846e7e","abstract_canon_sha256":"18c4425d9869d5a89c6fa31d7f3d03bc44cf174867ef342dd7b0c04b49837d93"},"schema_version":"1.0"},"canonical_sha256":"90b1c3f777186d1d0f372b2e8e7fb6d002475b52b199f6305ff7165f95390949","source":{"kind":"arxiv","id":"1709.00516","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.00516","created_at":"2026-05-18T00:36:07Z"},{"alias_kind":"arxiv_version","alias_value":"1709.00516v1","created_at":"2026-05-18T00:36:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.00516","created_at":"2026-05-18T00:36:07Z"},{"alias_kind":"pith_short_12","alias_value":"SCY4H53XDBWR","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SCY4H53XDBWR2DZX","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SCY4H53X","created_at":"2026-05-18T12:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:SCY4H53XDBWR2DZXFMXI475W2A","target":"record","payload":{"canonical_record":{"source":{"id":"1709.00516","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-02T01:38:34Z","cross_cats_sorted":[],"title_canon_sha256":"23a466c8003377c54523d8299cd1c62ac61071afda9c2b54e11fab8200846e7e","abstract_canon_sha256":"18c4425d9869d5a89c6fa31d7f3d03bc44cf174867ef342dd7b0c04b49837d93"},"schema_version":"1.0"},"canonical_sha256":"90b1c3f777186d1d0f372b2e8e7fb6d002475b52b199f6305ff7165f95390949","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:36:07.859943Z","signature_b64":"k5km9TKhcUHjO6107uINDdWsKiocFZ87IYzOx87wanmiAuUGmlA6sRlPb3UAsIOBbMGz/JYtbt4b3J5a3ttIBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90b1c3f777186d1d0f372b2e8e7fb6d002475b52b199f6305ff7165f95390949","last_reissued_at":"2026-05-18T00:36:07.859171Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:36:07.859171Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.00516","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":"2026-05-18T00:36:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rZAcUboUzzYamtnv6tsXNrvRQPCpC+8j+yHTc4/VJG/PWYU0CDsSoHNicuPZRrtkUf7K5rGrnnv2GFIPfEgIAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T17:51:01.498247Z"},"content_sha256":"567cce11635502b2af12c95a2d9de367f425b0ea4531c628c3075d8e513ea713","schema_version":"1.0","event_id":"sha256:567cce11635502b2af12c95a2d9de367f425b0ea4531c628c3075d8e513ea713"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:SCY4H53XDBWR2DZXFMXI475W2A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Gaussian Filter in CRF Based Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jing Li, Kai Cheng, Qisheng Wu, Yichi Gu","submitted_at":"2017-09-02T01:38:34Z","abstract_excerpt":"Artificial intelligence is making great changes in academy and industry with the fast development of deep learning, which is a branch of machine learning and statistical learning. Fully convolutional network [1] is the standard model for semantic segmentation. Conditional random fields coded as CNN [2] or RNN [3] and connected with FCN has been successfully applied in object detection [4]. In this paper, we introduce a multi-resolution neural network for FCN and apply Gaussian filter to the extended CRF kernel neighborhood and the label image to reduce the oscillating effect of CRF neural netw"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.00516","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":"2026-05-18T00:36:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NsJg7ftpSZ83bDXgIAB+J7fuAOO1je9w5TOfC4BZUsUgJ2fzSZHt7qtyb2vHQbRfq0brYcp5IihcacAEh7PaDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T17:51:01.498914Z"},"content_sha256":"645c27f48c998a8fdfcfb4d9a68c18fa338b89942cc4144245afa620fddc14f3","schema_version":"1.0","event_id":"sha256:645c27f48c998a8fdfcfb4d9a68c18fa338b89942cc4144245afa620fddc14f3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SCY4H53XDBWR2DZXFMXI475W2A/bundle.json","state_url":"https://pith.science/pith/SCY4H53XDBWR2DZXFMXI475W2A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SCY4H53XDBWR2DZXFMXI475W2A/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":"2026-06-08T17:51:01Z","links":{"resolver":"https://pith.science/pith/SCY4H53XDBWR2DZXFMXI475W2A","bundle":"https://pith.science/pith/SCY4H53XDBWR2DZXFMXI475W2A/bundle.json","state":"https://pith.science/pith/SCY4H53XDBWR2DZXFMXI475W2A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SCY4H53XDBWR2DZXFMXI475W2A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:SCY4H53XDBWR2DZXFMXI475W2A","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":"18c4425d9869d5a89c6fa31d7f3d03bc44cf174867ef342dd7b0c04b49837d93","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-02T01:38:34Z","title_canon_sha256":"23a466c8003377c54523d8299cd1c62ac61071afda9c2b54e11fab8200846e7e"},"schema_version":"1.0","source":{"id":"1709.00516","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.00516","created_at":"2026-05-18T00:36:07Z"},{"alias_kind":"arxiv_version","alias_value":"1709.00516v1","created_at":"2026-05-18T00:36:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.00516","created_at":"2026-05-18T00:36:07Z"},{"alias_kind":"pith_short_12","alias_value":"SCY4H53XDBWR","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SCY4H53XDBWR2DZX","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SCY4H53X","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:645c27f48c998a8fdfcfb4d9a68c18fa338b89942cc4144245afa620fddc14f3","target":"graph","created_at":"2026-05-18T00:36:07Z","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":"Artificial intelligence is making great changes in academy and industry with the fast development of deep learning, which is a branch of machine learning and statistical learning. Fully convolutional network [1] is the standard model for semantic segmentation. Conditional random fields coded as CNN [2] or RNN [3] and connected with FCN has been successfully applied in object detection [4]. In this paper, we introduce a multi-resolution neural network for FCN and apply Gaussian filter to the extended CRF kernel neighborhood and the label image to reduce the oscillating effect of CRF neural netw","authors_text":"Jing Li, Kai Cheng, Qisheng Wu, Yichi Gu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-02T01:38:34Z","title":"Gaussian Filter in CRF Based Semantic Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.00516","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":"sha256:567cce11635502b2af12c95a2d9de367f425b0ea4531c628c3075d8e513ea713","target":"record","created_at":"2026-05-18T00:36:07Z","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":"18c4425d9869d5a89c6fa31d7f3d03bc44cf174867ef342dd7b0c04b49837d93","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-02T01:38:34Z","title_canon_sha256":"23a466c8003377c54523d8299cd1c62ac61071afda9c2b54e11fab8200846e7e"},"schema_version":"1.0","source":{"id":"1709.00516","kind":"arxiv","version":1}},"canonical_sha256":"90b1c3f777186d1d0f372b2e8e7fb6d002475b52b199f6305ff7165f95390949","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"90b1c3f777186d1d0f372b2e8e7fb6d002475b52b199f6305ff7165f95390949","first_computed_at":"2026-05-18T00:36:07.859171Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:36:07.859171Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"k5km9TKhcUHjO6107uINDdWsKiocFZ87IYzOx87wanmiAuUGmlA6sRlPb3UAsIOBbMGz/JYtbt4b3J5a3ttIBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:36:07.859943Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.00516","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:567cce11635502b2af12c95a2d9de367f425b0ea4531c628c3075d8e513ea713","sha256:645c27f48c998a8fdfcfb4d9a68c18fa338b89942cc4144245afa620fddc14f3"],"state_sha256":"e28d8dba08d44d0444faf152a0acbe18b4d49a5db753b64333009ee4b27e5e8f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rykk7xPlj1KKLQT3tttUyRkj9XKy9xc79kXjzd4mtYRL+ivmreNTc/Zi8PvRE/udX4//vKrkjhAcz3TB4sAJAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T17:51:01.502848Z","bundle_sha256":"8fe2d519673cf1453caf044d626e5824100c7e62f10a2ceac522e798acae3cbb"}}