{"public_id":"co_65969df5a2d47a19583bcaf166245c31","status":"active","merged_into_public_id":null,"resolved_public_id":"co_65969df5a2d47a19583bcaf166245c31","name":"multiple distortion categories","description":"More than one class of image degradation that an assessment method can handle.","aliases":[],"types":["evaluation setting"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"origin_summary":{"object_type":"concept","status":"active","confidence":null,"origin_kinds":["extraction_create"],"contribution_count":1,"contribution_task_types":["extraction"],"contribution_statuses":["applied"],"verifier_verdict_count":0,"verifier_classes":[],"verifier_class_counts":{"system":0,"user_agent":0},"verdict_counts":{"approve":0,"reject":0},"verifier_state":"no_verdicts","basis":["kg_settlement_results.decision_payload.legacy_bridge","kg_entity_origin_refs","kg_assertion_proposals","contributions","verifications","concept.status"],"limits":["ledger provenance is aggregated; raw contribution and verifier audit rows are not expanded","entity matching uses settlement bridge refs and edge commands"]},"papers":[{"corpus_id":497740,"title":"Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality","citation_count":1708,"url":"https://sah.borca.ai/papers/497740"}],"claims":[{"public_id":"cl_c024d152ed9c5f04ec3142ca80863e06","text":"DIIVINE can assess distorted images across multiple distortion categories, unlike most no-reference image quality assessment algorithms that are distortion-specific.","corpus_id":497740,"url":"https://sah.borca.ai/claims/cl_c024d152ed9c5f04ec3142ca80863e06"}],"related_concepts":[],"resolved_url":"https://sah.borca.ai/concepts/co_65969df5a2d47a19583bcaf166245c31","url":"https://sah.borca.ai/concepts/co_65969df5a2d47a19583bcaf166245c31"}