{"id":"W4386070857","doi":"10.11159/mvml23.113","title":"Logistics Box Recognition in Robotic De-Palletizing System with Combination of Cycle-GAN and Mask-RCNN","year":2023,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Automotive engineering; Artificial intelligence; Optoelectronics; Materials science; Engineering","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":[0.0004446789,0.0007932867,0.0005423354,0.0002698617,0.0001292105,0.0003503195,0.0009506145,0.0005360776,0.001156296],"category_scores_gemma":[0.0005650505,0.0003219125,0.000466766,0.0002173889,0.0002844406,0.0006630183,0.0005184401,0.0006674308,0.000414773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004539458,"about_ca_system_score_gemma":0.000505591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00321981,"about_ca_topic_score_gemma":0.004130228,"domain_scores_codex":[0.9997683,0.00002608961,0.000008152026,0.00008223735,0.00006801331,0.00004716566],"domain_scores_gemma":[0.9998254,0.00004562993,0.00001861696,0.00004000817,0.00005486903,0.00001553292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004970872,0.0001439476,0.002138127,0.0001184039,0.00007179396,0.0002766842,0.00008145911,0.5255792,0.05728635,0.002049782,0.004339146,0.407418],"study_design_scores_gemma":[0.000003515847,0.00004483328,0.0005035404,0.000003513782,0.000007341251,0.00004160498,0.000005710969,0.9906685,0.007932019,0.0003330728,0.0004501393,0.00000628547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1452427,0.0006060825,0.8435289,0.0002466936,0.0001552132,0.00009913685,0.0001855483,0.004756547,0.005179147],"genre_scores_gemma":[0.8261335,0.0002313572,0.1669375,0.0002541847,0.00003398213,0.00006237707,0.0004325893,0.0001364161,0.005778109],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00321981,"threshold_uncertainty_score":0.006402135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007979360110572325,"score_gpt":0.1886292792302275,"score_spread":0.1806499191196552,"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."}}