{"id":"W1510840923","doi":"10.1023/a:1015397423173","title":"A Multiplication-Free Algorithm and A Parallel Architecture for Affine Transformation","year":2002,"lang":"en","type":"article","venue":"The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"U.S. Department of Energy","keywords":"Computer science; Adder; Image warping; Mobile device; Affine transformation; MPEG-4; Architecture; CMOS; Computer architecture; Computer hardware; Latency (audio); Embedded system; Electronic engineering; Artificial intelligence; Coding (social sciences); Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001018121,0.0002238769,0.0004019244,0.0003718211,0.0003949504,0.0002074961,0.0008252697,0.0001636359,0.000001377289],"category_scores_gemma":[0.0001319964,0.0001485268,0.00008598953,0.0003989752,0.0002320902,0.001036353,0.0000909253,0.0003132914,4.045014e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002854117,"about_ca_system_score_gemma":0.00003401865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004219757,"about_ca_topic_score_gemma":8.663298e-7,"domain_scores_codex":[0.99852,0.00006593719,0.0006573725,0.0002287474,0.0002170911,0.0003108353],"domain_scores_gemma":[0.99807,0.0004082124,0.0006135162,0.0002589813,0.0005738077,0.00007545428],"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":[0.00008371575,0.00005578401,0.000003070771,0.0002941859,0.00004165476,0.000004043844,0.0009330428,0.00007695225,0.02505242,0.001335012,0.000778915,0.9713412],"study_design_scores_gemma":[0.004408246,0.003320549,0.00001361101,0.0008125835,0.0002057586,0.003963235,0.0008197156,0.7874882,0.06130371,0.1158893,0.02117367,0.0006013461],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003662825,0.01504074,0.9789088,0.004651,0.00003299839,0.0008265263,0.00001380053,0.0001362945,0.00002356199],"genre_scores_gemma":[0.4856248,0.001001545,0.5126761,0.0001967992,0.0002226206,0.0001434564,0.000001962855,0.00003338483,0.00009933839],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9707398,"threshold_uncertainty_score":0.6056749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01618833907587678,"score_gpt":0.2689606926107966,"score_spread":0.2527723535349198,"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."}}