{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:LHI33S3DAXHHDEOFBNB3HHWY6P","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":"8b1017bfb2d3d972c6fb645e95ad24715b1aca1d4fded4f118c0f5601859dc30","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-02-01T16:14:57Z","title_canon_sha256":"beb9c47092d24fe539237e45394d5177532d0784ce30f04b654b7901846413c7"},"schema_version":"1.0","source":{"id":"1602.00577","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.00577","created_at":"2026-05-18T01:21:33Z"},{"alias_kind":"arxiv_version","alias_value":"1602.00577v1","created_at":"2026-05-18T01:21:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.00577","created_at":"2026-05-18T01:21:33Z"},{"alias_kind":"pith_short_12","alias_value":"LHI33S3DAXHH","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_16","alias_value":"LHI33S3DAXHHDEOF","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_8","alias_value":"LHI33S3D","created_at":"2026-05-18T12:30:29Z"}],"graph_snapshots":[{"event_id":"sha256:805eafd2cab914d75f59e4bc7ff904d50a4fac18e98bee2f63fc0b3eff5448a2","target":"graph","created_at":"2026-05-18T01:21:33Z","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 propose a fast deep learning method for object saliency detection using convolutional neural networks. In our approach, we use a gradient descent method to iteratively modify the input images based on the pixel-wise gradients to reduce a pre-defined cost function, which is defined to measure the class-specific objectness and clamp the class-irrelevant outputs to maintain image background. The pixel-wise gradients can be efficiently computed using the back-propagation algorithm. We further apply SLIC superpixels and LAB color based low level saliency features to smooth and ref","authors_text":"Hengyue Pan, Hui Jiang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-02-01T16:14:57Z","title":"A Deep Learning Based Fast Image Saliency Detection Algorithm"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.00577","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":"sha256:799e1735864e9412efcde60bb909f42374711b9c8b1f06f8e62d54395927cc35","target":"record","created_at":"2026-05-18T01:21:33Z","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":"8b1017bfb2d3d972c6fb645e95ad24715b1aca1d4fded4f118c0f5601859dc30","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-02-01T16:14:57Z","title_canon_sha256":"beb9c47092d24fe539237e45394d5177532d0784ce30f04b654b7901846413c7"},"schema_version":"1.0","source":{"id":"1602.00577","kind":"arxiv","version":1}},"canonical_sha256":"59d1bdcb6305ce7191c50b43b39ed8f3e514d89286266456f788d42105bd2660","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59d1bdcb6305ce7191c50b43b39ed8f3e514d89286266456f788d42105bd2660","first_computed_at":"2026-05-18T01:21:33.350516Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:21:33.350516Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ddlhWqOtq23cVKuRQqOZ2pzENnuizSg2mIDVB1IGUITme0ftj4Z1dgkLzSnG5e06aqMTrQWetxzQ+kL90NA0AA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:21:33.351188Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.00577","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:799e1735864e9412efcde60bb909f42374711b9c8b1f06f8e62d54395927cc35","sha256:805eafd2cab914d75f59e4bc7ff904d50a4fac18e98bee2f63fc0b3eff5448a2"],"state_sha256":"182d7913a4924debbbc3827e7422840c4ad891b97917aee07114cefe10404b0f"}