{"id":"W4382395103","doi":"10.18280/ts.400315","title":"Enhancing Real-Time Image Transmission in Wireless Sensor Networks: A Study on Energy-Efficient Compression Algorithms","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Wireless sensor network; Transmission (telecommunications); Energy (signal processing); Data compression; Algorithm; Image compression; Real-time computing; Image (mathematics); Wireless; Compression (physics); Computer vision; Computer network; Telecommunications; Image processing; Mathematics; Statistics; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006808488,0.000510264,0.0003366847,0.0005969591,0.0001625985,0.0006611005,0.0004618783,0.0005799505,0.0006367441],"category_scores_gemma":[0.002343933,0.0001758264,0.0003028495,0.0008609531,0.0005601363,0.001183856,0.000273784,0.0005055165,0.0001862948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003069745,"about_ca_system_score_gemma":0.0003232004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006346869,"about_ca_topic_score_gemma":0.0004654528,"domain_scores_codex":[0.9996141,0.0001228167,0.00002201383,0.00004841244,0.0001685556,0.00002416951],"domain_scores_gemma":[0.9991089,0.0005640807,0.00008527641,0.00007262676,0.0001552129,0.00001395879],"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":[0.0001857374,0.0001846824,0.001496524,0.0007330795,0.00009794572,0.0002738274,0.0003998943,0.3508798,0.07867243,0.1053978,0.001329139,0.4603492],"study_design_scores_gemma":[0.000007306102,0.0002028976,0.0006866053,0.00005711835,0.000024557,0.000453099,0.00006080982,0.9677764,0.02052303,0.006037274,0.004151764,0.00001917088],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04121532,0.01077807,0.9425994,0.0003151069,0.00009791503,0.00003947781,0.00001437963,0.00007256075,0.004867749],"genre_scores_gemma":[0.6691177,0.0309481,0.2930139,0.0001448013,0.0003318378,0.00009378563,0.00006907871,0.00008051134,0.006200241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006808488,"threshold_uncertainty_score":0.003600717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01278594187895002,"score_gpt":0.243917751317921,"score_spread":0.231131809438971,"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."}}