{"id":"W3019880883","doi":"10.1109/access.2020.2989267","title":"Analysis and Comparison of FPGA-Based Histogram of Oriented Gradients Implementations","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; University of Victoria","keywords":"Computer science; Histogram; Field-programmable gate array; Histogram matching; Normalization (sociology); Algorithm; Computation; Histogram of oriented gradients; Pixel; Computer engineering; Artificial intelligence; Computer hardware; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00002227736,0.00006405703,0.0002041877,0.0001156165,0.00001807771,0.00001115412,0.00009925781,0.00001409589,0.00003331385],"category_scores_gemma":[0.000008873137,0.00006723416,0.00005399417,0.0006818823,0.00003160109,0.00006735197,0.0000104043,0.00004088848,6.147897e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001108801,"about_ca_system_score_gemma":0.000005270991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001920578,"about_ca_topic_score_gemma":0.0001076273,"domain_scores_codex":[0.9994995,0.00000953905,0.0002219352,0.00008745305,0.00009765447,0.00008390081],"domain_scores_gemma":[0.9997374,0.00002689092,0.00005466572,0.00009342721,0.0000386644,0.00004890897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001460617,0.00006603415,0.9011008,0.0001901054,0.0004121807,9.975095e-7,0.001537702,0.07896114,0.01082238,0.00002148733,0.001012286,0.005860329],"study_design_scores_gemma":[0.00102855,0.0000703678,0.1890057,0.0000206177,0.000858078,1.49692e-7,0.0004020814,0.488761,0.3181145,0.00001519096,0.001493826,0.0002300212],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971505,0.0000525587,0.02804739,0.00005183934,0.00006967795,0.00006051983,0.00004268326,0.00005237422,0.0001179052],"genre_scores_gemma":[0.9994998,0.000003406328,0.000419129,0.00002955787,0.00001036811,0.000002955114,0.0000249021,0.000007886099,0.000002017434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7120951,"threshold_uncertainty_score":0.274173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03665021908823723,"score_gpt":0.3338171250800423,"score_spread":0.2971669059918051,"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."}}