{"id":"W2050819065","doi":"10.1109/icspcs.2014.7021058","title":"2×2 Panoramic camera array stitching using edge matching","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Image stitching; Panorama; Scale-invariant feature transform; Computer vision; Artificial intelligence; Computer science; Matching (statistics); Enhanced Data Rates for GSM Evolution; Feature matching; Feature (linguistics); Invariant (physics); Feature extraction; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002281562,0.0004130884,0.000366334,0.0008214837,0.0002540597,0.0005622507,0.0005955427,0.0005025601,0.008298694],"category_scores_gemma":[0.0006233928,0.0002619552,0.0003658456,0.0008040955,0.0001908963,0.0008503185,0.0004931916,0.000414612,0.002250953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002065928,"about_ca_system_score_gemma":0.0002706693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009108646,"about_ca_topic_score_gemma":0.001625903,"domain_scores_codex":[0.9996839,0.0000245694,0.00001682628,0.00007857967,0.0001633408,0.00003278094],"domain_scores_gemma":[0.9997402,0.00004318176,0.00003125302,0.00007585324,0.0000951912,0.00001435365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001566237,0.00005744735,0.0008225496,0.0001102771,0.00003367363,0.0001133661,0.00006611866,0.004931896,0.1907853,0.002153929,0.003057915,0.7977107],"study_design_scores_gemma":[0.00005937651,0.0004302176,0.01209245,0.00004383807,0.00007807628,0.002767054,0.0001346357,0.3942695,0.5092489,0.002594032,0.07816869,0.0001132199],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03106758,0.0002867371,0.9599263,0.00005777769,0.0001055653,0.00006490949,0.0001125343,0.002098273,0.006280379],"genre_scores_gemma":[0.1421004,0.0002503501,0.8498764,0.00008365764,0.00006038721,0.00004989808,0.000284889,0.0002292881,0.007064817],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008298694,"threshold_uncertainty_score":0.02776188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03063795919640527,"score_gpt":0.3083349745415288,"score_spread":0.2776970153451235,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}