{"id":"W4319990913","doi":"10.18280/ts.390629","title":"Salient Target Detection Method of Video Images Based on Convolution Neural Network","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"People's Government of Jilin Province","keywords":"Computer science; Artificial intelligence; Salient; Convolution (computer science); Pattern recognition (psychology); Computer vision; Foreground detection; Image (mathematics); Convolutional neural network; Artificial neural network; Object detection","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003220313,0.0004812177,0.000525563,0.0004007043,0.0002191715,0.0004239727,0.0006217376,0.0005280459,0.0007853332],"category_scores_gemma":[0.0006855756,0.0002102025,0.0004751291,0.0003531681,0.0003552303,0.000765703,0.0003775585,0.0004881204,0.0001594039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005486319,"about_ca_system_score_gemma":0.0004545999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003796825,"about_ca_topic_score_gemma":0.002564496,"domain_scores_codex":[0.99981,0.00003088394,0.000008448015,0.00006076136,0.00006290466,0.00002689561],"domain_scores_gemma":[0.9998457,0.00005526196,0.00002391813,0.00001189118,0.00005330963,0.000009886017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002620463,0.0001061012,0.001996358,0.0001711531,0.00009245417,0.0001846919,0.0001533395,0.5473259,0.08583716,0.01449511,0.001268576,0.3481071],"study_design_scores_gemma":[0.00000156306,0.00001905407,0.0001686989,0.000001472041,0.000004586328,0.00002386349,0.000003174143,0.9961139,0.003073165,0.0004487557,0.0001386584,0.000003044464],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02854512,0.0001979846,0.9698542,0.00006449601,0.00002641819,0.00002327341,0.00001474853,0.0001814326,0.00109224],"genre_scores_gemma":[0.7769529,0.0004896085,0.2180007,0.00007572657,0.00004206313,0.00007235196,0.00008383031,0.00003899408,0.004243772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003796825,"threshold_uncertainty_score":0.007549405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0288416196667417,"score_gpt":0.2659051484954049,"score_spread":0.2370635288286632,"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."}}