{"id":"W2164701340","doi":"10.1109/mnnfs.1996.493811","title":"VIP: an FPGA-based processor for image processing and neural networks","year":2002,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; SIMD; Field-programmable gate array; Multiprocessing; Artificial neural network; Parallel computing; Computer architecture; Image processing; Architecture; Embedded system; Image (mathematics); Computer hardware; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001314514,0.0003818064,0.0002241442,0.000358732,0.0001653496,0.0003597752,0.0007189829,0.0002359189,0.009716465],"category_scores_gemma":[0.000210916,0.0001585211,0.000167374,0.000370703,0.0001814089,0.0003945012,0.0003112541,0.0004116621,0.002264536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001634672,"about_ca_system_score_gemma":0.000193813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002962846,"about_ca_topic_score_gemma":0.0004241105,"domain_scores_codex":[0.9999031,0.00001251738,0.000005500011,0.00002070595,0.0000399686,0.00001826068],"domain_scores_gemma":[0.9999384,0.00001210675,0.00000588174,0.0000125676,0.00002100338,0.00001016958],"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":[0.000986049,0.00008870662,0.001671015,0.0005971755,0.000092681,0.0005731428,0.00008513439,0.02698241,0.1671487,0.02287349,0.04059688,0.7383047],"study_design_scores_gemma":[0.0004416611,0.002511535,0.006961571,0.000115802,0.0001840942,0.003956731,0.0001163907,0.3274346,0.2764694,0.01271291,0.3689782,0.0001170396],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06390329,0.002301721,0.8843948,0.0002152875,0.0005463231,0.000246955,0.0009774779,0.01505339,0.03236077],"genre_scores_gemma":[0.3579751,0.001084918,0.6141227,0.0002535344,0.0001551914,0.000205224,0.002439419,0.0004101623,0.0233537],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009716465,"threshold_uncertainty_score":0.0325048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210903632928531,"score_gpt":0.2186263407957759,"score_spread":0.2065173044664906,"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."}}