{"id":"W4396532494","doi":"10.22215/etd/2023-15941","title":"On-camera Hardware Accelerated Visual SLAM","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Mitacs","keywords":"Computer graphics (images); Computer science; Computer vision; Artificial intelligence; Computer hardware","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002782879,0.0005571996,0.0004165892,0.0004030823,0.0002356075,0.0007413399,0.0009495201,0.0003441655,0.01022171],"category_scores_gemma":[0.001293213,0.0001899335,0.0002597435,0.0004813984,0.0001825766,0.0007116459,0.001053927,0.0005983203,0.001991417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005523941,"about_ca_system_score_gemma":0.000942009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005877075,"about_ca_topic_score_gemma":0.00940542,"domain_scores_codex":[0.9994571,0.00004386542,0.00001042566,0.00008061754,0.0002819384,0.0001260744],"domain_scores_gemma":[0.9993729,0.00009572437,0.00003624687,0.0001987918,0.0002553616,0.00004113043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009752952,0.0003531275,0.004521972,0.0006271616,0.00007724919,0.0003032761,0.0003436401,0.1192425,0.1055533,0.006846694,0.03136221,0.7297937],"study_design_scores_gemma":[0.0001600416,0.0009672667,0.01268204,0.0001245725,0.00005865992,0.0004983592,0.0003504994,0.817692,0.0944526,0.00485174,0.06809381,0.00006845115],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2654761,0.0007396589,0.644592,0.0003673697,0.0004826539,0.0003191788,0.001170975,0.01469086,0.07216115],"genre_scores_gemma":[0.8086581,0.0002596015,0.1760595,0.0001091588,0.00003299337,0.000114547,0.001221991,0.0004961001,0.01304795],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01022171,"threshold_uncertainty_score":0.03419507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01861732878581469,"score_gpt":0.2698814802435436,"score_spread":0.2512641514577289,"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."}}