{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:LHNX5VDD2AOJX3H7SOTKF57P74","short_pith_number":"pith:LHNX5VDD","schema_version":"1.0","canonical_sha256":"59db7ed463d01c9becff93a6a2f7efff1dbc21ba25ea615e778781ced2b463d8","source":{"kind":"arxiv","id":"1706.05358","version":1},"attestation_state":"computed","paper":{"title":"Local Feature Descriptor Learning with Adaptive Siamese Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Chong Huang, Kwang-Ting (Tim) Cheng, Qiong Liu, Yan-Ying Chen","submitted_at":"2017-06-16T17:27:41Z","abstract_excerpt":"Although the recent progress in the deep neural network has led to the development of learnable local feature descriptors, there is no explicit answer for estimation of the necessary size of a neural network. Specifically, the local feature is represented in a low dimensional space, so the neural network should have more compact structure. The small networks required for local feature descriptor learning may be sensitive to initial conditions and learning parameters and more likely to become trapped in local minima. In order to address the above problem, we introduce an adaptive pruning Siames"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1706.05358","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-16T17:27:41Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"feec6d9c830ae57bcc2525a0afca5fed8cf4612a60189c04f9aa942fee37f411","abstract_canon_sha256":"576b39697d39e7ad4bc72e002044e79683c1ea5adee8e8269105219f97e55aae"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:42:13.981465Z","signature_b64":"ODJBsu6mKqQ7V+/dEuoaqkemVNd2xUK2c4KJm1rR12Q+P6t1meU8tVrhjZeJWSvTJnnJLStnaMSGzuFj2JBMDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59db7ed463d01c9becff93a6a2f7efff1dbc21ba25ea615e778781ced2b463d8","last_reissued_at":"2026-05-18T00:42:13.980712Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:42:13.980712Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Local Feature Descriptor Learning with Adaptive Siamese Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Chong Huang, Kwang-Ting (Tim) Cheng, Qiong Liu, Yan-Ying Chen","submitted_at":"2017-06-16T17:27:41Z","abstract_excerpt":"Although the recent progress in the deep neural network has led to the development of learnable local feature descriptors, there is no explicit answer for estimation of the necessary size of a neural network. Specifically, the local feature is represented in a low dimensional space, so the neural network should have more compact structure. The small networks required for local feature descriptor learning may be sensitive to initial conditions and learning parameters and more likely to become trapped in local minima. In order to address the above problem, we introduce an adaptive pruning Siames"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.05358","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1706.05358","created_at":"2026-05-18T00:42:13.980822+00:00"},{"alias_kind":"arxiv_version","alias_value":"1706.05358v1","created_at":"2026-05-18T00:42:13.980822+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.05358","created_at":"2026-05-18T00:42:13.980822+00:00"},{"alias_kind":"pith_short_12","alias_value":"LHNX5VDD2AOJ","created_at":"2026-05-18T12:31:28.150371+00:00"},{"alias_kind":"pith_short_16","alias_value":"LHNX5VDD2AOJX3H7","created_at":"2026-05-18T12:31:28.150371+00:00"},{"alias_kind":"pith_short_8","alias_value":"LHNX5VDD","created_at":"2026-05-18T12:31:28.150371+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74","json":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74.json","graph_json":"https://pith.science/api/pith-number/LHNX5VDD2AOJX3H7SOTKF57P74/graph.json","events_json":"https://pith.science/api/pith-number/LHNX5VDD2AOJX3H7SOTKF57P74/events.json","paper":"https://pith.science/paper/LHNX5VDD"},"agent_actions":{"view_html":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74","download_json":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74.json","view_paper":"https://pith.science/paper/LHNX5VDD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1706.05358&json=true","fetch_graph":"https://pith.science/api/pith-number/LHNX5VDD2AOJX3H7SOTKF57P74/graph.json","fetch_events":"https://pith.science/api/pith-number/LHNX5VDD2AOJX3H7SOTKF57P74/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74/action/storage_attestation","attest_author":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74/action/author_attestation","sign_citation":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74/action/citation_signature","submit_replication":"https://pith.science/pith/LHNX5VDD2AOJX3H7SOTKF57P74/action/replication_record"}},"created_at":"2026-05-18T00:42:13.980822+00:00","updated_at":"2026-05-18T00:42:13.980822+00:00"}