{"id":"W4388135218","doi":"10.21275/sr231026061252","title":"An Evaluation of a Haar Cascade Classifiers using Multi-Resolution Images and Multi-Threading Resources on a Raspberry Pi","year":2023,"lang":"en","type":"article","venue":"International Journal of Science and Research (IJSR)","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kwantlen Polytechnic University","funders":"","keywords":"Haar-like features; Raspberry pi; Threading (protein sequence); Cascade; Computer science; Artificial intelligence; Haar; Pattern recognition (psychology); Resolution (logic); Physics; World Wide Web; Chromatography; Chemistry; Internet of Things","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":[0.0111448,0.00009304145,0.0001402502,0.00187122,0.0003479625,0.0003557945,0.001489114,0.0000489545,0.000003135546],"category_scores_gemma":[0.001926337,0.00007215642,0.00003040931,0.001048639,0.001210631,0.002601773,0.0005914342,0.0003446729,0.000001444153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002468982,"about_ca_system_score_gemma":0.0004159545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007075594,"about_ca_topic_score_gemma":0.000004281875,"domain_scores_codex":[0.9950036,0.0003129705,0.0003658656,0.00034477,0.003680145,0.0002925803],"domain_scores_gemma":[0.9959196,0.0002770206,0.0002798151,0.0002366509,0.003095167,0.0001916951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001049866,0.0001870972,0.001723754,0.00001440674,0.00002730208,0.00006425031,0.003042452,0.005025992,0.8433413,0.001044356,0.0002891728,0.145135],"study_design_scores_gemma":[0.0006894124,0.0002329166,0.02021135,0.0003508386,0.000004873328,0.0001054992,0.000939491,0.9016899,0.07351702,0.002028289,0.0001372506,0.00009315254],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8451493,0.0002460022,0.1533303,0.000775705,0.0002484171,0.0001642952,0.000009657158,0.0000314306,0.00004489511],"genre_scores_gemma":[0.922702,0.0002287113,0.0769365,0.00003140933,0.00007184516,0.000004315157,8.515664e-7,0.000005530636,0.00001883889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8966639,"threshold_uncertainty_score":0.4460621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2688884357160474,"score_gpt":0.5146405240653702,"score_spread":0.2457520883493228,"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."}}