{"id":"W7129600956","doi":"10.1109/iceconf65644.2025.11379554","title":"Design of Hardware Accelerator Structure on FPGA for Real-Time Image Classification through Optimised Convolution Layer","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Field-programmable gate array; Convolution (computer science); Key (lock); Loop unrolling; Deep learning; Hardware acceleration; Inference; Latency (audio); Gate array","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000227174,0.0004754115,0.0005525565,0.0001676565,0.000504689,0.0001943442,0.001297543,0.0003223832,0.0002075831],"category_scores_gemma":[0.0001055691,0.0004620706,0.0001765123,0.001410562,0.000245174,0.001057055,0.0002180734,0.0002734182,0.00004895551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000273176,"about_ca_system_score_gemma":0.0004190154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009118287,"about_ca_topic_score_gemma":0.000001514224,"domain_scores_codex":[0.9966214,0.0002143546,0.000941388,0.001275945,0.0003694485,0.0005774782],"domain_scores_gemma":[0.9958839,0.0008483623,0.0006229715,0.001633666,0.0009023743,0.0001087147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003850186,0.0002481502,0.00000562133,0.0001363605,0.00008837801,7.103832e-7,0.0002843787,0.04596512,0.7170653,0.190451,0.0266162,0.01875369],"study_design_scores_gemma":[0.001158836,0.0002680644,0.0003180135,0.0001113029,0.00007012148,0.000001286204,0.0000387922,0.6740194,0.3025557,0.01938157,0.001722713,0.0003542493],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009469149,0.00008961557,0.9885078,0.003255476,0.0004157102,0.003739293,0.0001241989,0.0002366058,0.002684401],"genre_scores_gemma":[0.3082779,0.0002781544,0.6867226,0.0006996025,0.0001345311,0.0003913564,0.00007922266,0.0000395899,0.003377113],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6280543,"threshold_uncertainty_score":0.9997831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06347135336073978,"score_gpt":0.326068601569163,"score_spread":0.2625972482084232,"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."}}