{"id":"W2134412393","doi":"10.1109/icassp.2008.4517830","title":"Near lossless image compression by local packing of histogram","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Lossless compression; Histogram; Pixel; Image compression; Artificial intelligence; Computer science; Data compression; Histogram matching; Algorithm; Computer vision; Entropy (arrow of time); Lossy compression; Pattern recognition (psychology); Color Cell Compression; Mathematics; Image (mathematics); Image processing","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":[0.000224207,0.0002262276,0.0003931324,0.0005897372,0.0002540348,0.0005196433,0.0004662237,0.00026918,0.001250053],"category_scores_gemma":[0.001017573,0.0001999719,0.0001996383,0.0006730132,0.0005179215,0.001417858,0.0006068379,0.000429938,0.0005236352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002386666,"about_ca_system_score_gemma":0.000179536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003106357,"about_ca_topic_score_gemma":0.0003306485,"domain_scores_codex":[0.9997588,0.00003554124,0.0000103455,0.00002964274,0.0001471324,0.00001850221],"domain_scores_gemma":[0.999631,0.0001220964,0.00005492674,0.0001082067,0.0000627313,0.00002103264],"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":[0.00064755,0.000166899,0.001259242,0.0002067347,0.00004447018,0.0003751469,0.0002463971,0.0784946,0.1835535,0.02514409,0.002504286,0.707357],"study_design_scores_gemma":[0.00006775962,0.0004585696,0.001814595,0.00003304927,0.00003471089,0.001507029,0.00007375192,0.787117,0.1847618,0.0156984,0.008379391,0.00005405757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05361084,0.0004897037,0.9433983,0.00009123815,0.00005006261,0.00003871166,0.00002659454,0.0006758955,0.001618658],"genre_scores_gemma":[0.5744075,0.0005364901,0.4207512,0.0001522547,0.0001038316,0.0000648804,0.0001673962,0.0001475955,0.003669008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001250053,"threshold_uncertainty_score":0.004181862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01296839157287192,"score_gpt":0.2579508752178314,"score_spread":0.2449824836449595,"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."}}