{"id":"W2000095678","doi":"10.1007/s11265-007-0050-0","title":"A Novel Application-specific Instruction-set Processor Design Approach for Video Processing Acceleration","year":2007,"lang":"en","type":"article","venue":"The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Instruction set; Video processing; Overhead (engineering); Flexibility (engineering); Computer architecture; Set (abstract data type); Application-specific instruction-set processor; Embedded system; Hardware acceleration; Parallel computing; Computer hardware; Computer engineering; Field-programmable gate array; Programming language","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":[0.0001477532,0.0006905108,0.0003704087,0.0006743351,0.0004444077,0.0006237621,0.00160176,0.0003671969,0.004978062],"category_scores_gemma":[0.0003731464,0.0002742776,0.0004029768,0.0006884069,0.0001632893,0.0006555563,0.0003834778,0.000853192,0.001522569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004005353,"about_ca_system_score_gemma":0.00087826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001173997,"about_ca_topic_score_gemma":0.003857204,"domain_scores_codex":[0.9997651,0.00002405012,0.00001752658,0.00004144612,0.000111094,0.00004084077],"domain_scores_gemma":[0.999764,0.00003554271,0.00001881644,0.00003803907,0.0001281184,0.00001544744],"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":[0.0003664857,0.0002627862,0.00105528,0.0003514301,0.000130328,0.000289765,0.0001339985,0.0203009,0.2844247,0.01969874,0.01908895,0.6538966],"study_design_scores_gemma":[0.0001175669,0.001160362,0.001151038,0.0000631478,0.0002297394,0.001046027,0.00006357751,0.6253039,0.2954966,0.00850669,0.0667881,0.00007321984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03338479,0.001044642,0.9480409,0.000241336,0.000307089,0.0001492214,0.000123331,0.005993288,0.01071542],"genre_scores_gemma":[0.2892866,0.0007397245,0.6929466,0.0005369602,0.0002200961,0.0002680198,0.0006016222,0.0003018047,0.01509864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004978062,"threshold_uncertainty_score":0.0166533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02574094647433939,"score_gpt":0.2606054465933372,"score_spread":0.2348645001189978,"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."}}