{"id":"W2165387203","doi":"10.1049/cp.2011.1065","title":"A hybrid image compression technique based on DWT and DCT transforms","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Discrete cosine transform; Image compression; Computer science; Transform coding; Computer vision; Data compression; Artificial intelligence; Compression (physics); Image (mathematics); Texture compression; Image processing; Materials science","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":[0.0002049767,0.0001998879,0.0001820325,0.0001757252,0.000114121,0.00006013925,0.000872494,0.00005416096,0.0001110379],"category_scores_gemma":[0.00001737359,0.0001412308,0.00004608385,0.0001379929,0.00008376651,0.0008815597,0.0002444714,0.0001948677,0.00001838445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001885391,"about_ca_system_score_gemma":0.00002303784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003095027,"about_ca_topic_score_gemma":0.000001049153,"domain_scores_codex":[0.9987278,0.00005366949,0.0002198442,0.000505241,0.0002405372,0.0002528937],"domain_scores_gemma":[0.99876,0.00006970068,0.00006373145,0.000924661,0.00004696853,0.0001349677],"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":[0.0002404276,0.001040756,0.0003308164,0.0001327166,0.00001547629,0.0002776117,0.0004768973,0.00001144584,0.3320725,0.1206032,0.02018759,0.5246106],"study_design_scores_gemma":[0.000287032,0.0002646791,0.0003980025,0.0001067744,0.000002013136,0.00002520048,0.000003343594,0.03415364,0.9361407,0.02465371,0.003708234,0.0002567292],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004823392,0.00001446343,0.9742116,0.0001479057,0.00004267419,0.0004610654,0.00000994588,0.001209829,0.02342017],"genre_scores_gemma":[0.3316884,0.00001253585,0.6675852,0.0005241613,0.000007035171,0.00009795935,0.000004225015,0.00001216803,0.00006828357],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6040682,"threshold_uncertainty_score":0.5759224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01943484091797808,"score_gpt":0.2517754528516414,"score_spread":0.2323406119336633,"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."}}