{"id":"W2360103243","doi":"","title":"An Algorithm for Fast Creating Panoramic Image and Its Implementation","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Image stitching; Computer science; Computer vision; Artificial intelligence; Rendering (computer graphics); Image (mathematics); Algorithm; Template matching; Similarity (geometry); Image processing; Computer graphics (images)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008249167,0.0001159849,0.00009573228,0.00008126186,0.0003363837,0.0002932198,0.0003309788,0.00002216604,0.000003393344],"category_scores_gemma":[1.61571e-7,0.0001223836,0.00003028542,0.000189116,0.00001821714,0.0007098646,0.0001038114,0.00004854561,0.00001326086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002605766,"about_ca_system_score_gemma":0.00001854667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001991504,"about_ca_topic_score_gemma":0.000004606751,"domain_scores_codex":[0.9990721,0.00001561233,0.0002143164,0.0004134949,0.00007081126,0.0002136294],"domain_scores_gemma":[0.9994797,0.00004161474,0.00008484481,0.0002244066,0.0001125025,0.00005696154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[2.219581e-7,0.0000384019,0.00002988522,0.00000542628,0.000002198318,1.86963e-7,0.0001062323,0.00001503993,0.0629519,0.009121391,0.0002326246,0.9274965],"study_design_scores_gemma":[0.0006370604,0.0000435667,0.001788325,0.000007063369,0.000005819178,0.00002195633,0.00007440085,0.8801451,0.03146821,0.008354709,0.07719336,0.0002604274],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001134096,0.000107767,0.997465,0.000235259,0.00001139758,0.0007159968,0.00002559398,0.0001919931,0.0001129064],"genre_scores_gemma":[0.01273141,0.000006542291,0.9863486,0.0002673809,0.0001564578,0.0003336121,0.00008839773,0.00001266316,0.00005499035],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9272361,"threshold_uncertainty_score":0.4990659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007058526130274016,"score_gpt":0.3104232817957878,"score_spread":0.3033647556655138,"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."}}