{"id":"W2162377461","doi":"10.1109/have.2003.1244721","title":"Neural network architecture for 3D object representation","year":2004,"lang":"en","type":"article","venue":"","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Morphing; Object (grammar); Representation (politics); Artificial intelligence; Artificial neural network; Set (abstract data type); Feedforward neural network; Computer vision; Architecture; Cognitive neuroscience of visual object recognition; Object model; Transformation (genetics)","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":[0.00007635432,0.00005820989,0.0000598686,0.00003216923,0.0001471743,0.0001320919,0.0001675885,0.00002795218,0.000002619085],"category_scores_gemma":[0.00001995277,0.00004682944,0.00003941821,0.0001967133,0.00002092885,0.0002535929,0.00003055692,0.0000581309,0.000005608946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001241571,"about_ca_system_score_gemma":0.00004880612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001908298,"about_ca_topic_score_gemma":0.00001528368,"domain_scores_codex":[0.9994569,0.00001257136,0.00009280813,0.0002038103,0.00007406242,0.000159832],"domain_scores_gemma":[0.9997022,0.00002881508,0.00003856457,0.0001607555,0.00004235786,0.00002730422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008143403,0.00001106789,0.0001598518,0.00001205424,0.000005888029,0.000001532406,0.0003113041,0.07488662,0.0002536519,0.00832493,0.0006932914,0.9153317],"study_design_scores_gemma":[0.002107896,0.0002568116,0.00174999,0.00005754668,0.00001739424,0.0005348765,0.00006506988,0.5585737,0.01798111,0.4133392,0.004799547,0.0005168893],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004444005,0.00005379301,0.9909922,0.001354387,0.0006407604,0.0001047192,2.016991e-7,0.0002003699,0.002209496],"genre_scores_gemma":[0.2101487,0.00000130099,0.7888424,0.0003571376,0.0002821038,0.00001363436,0.000002172811,0.000004130022,0.0003484547],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9148148,"threshold_uncertainty_score":0.1909649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01399667446774282,"score_gpt":0.2606697797174756,"score_spread":0.2466731052497327,"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."}}