{"id":"W7110844513","doi":"10.1109/icjece.2025.3618647","title":"A New Singular Vector Sparse Representation Technique for Crop Image Compression","year":2025,"lang":"","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wavelet; Image compression; Pattern recognition (psychology); Compression ratio; Compressed sensing; Singular value decomposition; Wavelet transform; Data compression; Singular value; Iterative reconstruction","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003193223,0.0003633682,0.0006090328,0.001137698,0.0002473843,0.0005416785,0.00101458,0.0002118518,0.00001061493],"category_scores_gemma":[0.0002852551,0.0003621716,0.000201093,0.001101025,0.00005260112,0.0008234601,0.0001795094,0.0006580143,7.055248e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002720143,"about_ca_system_score_gemma":0.001400468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003919388,"about_ca_topic_score_gemma":0.00003297426,"domain_scores_codex":[0.9976779,0.00007369928,0.0008635758,0.0004948155,0.0002257108,0.000664292],"domain_scores_gemma":[0.9974126,0.00039195,0.0003251425,0.0004549726,0.0004319105,0.000983414],"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":[0.0001445377,0.0000961638,0.0002624934,0.0003926852,0.0002714015,0.0005569028,0.0003917819,0.01024359,0.0960957,0.0418466,0.06460162,0.7850965],"study_design_scores_gemma":[0.001108493,0.0007309511,0.001219789,0.001816621,0.00008120646,0.000415379,0.000002205977,0.8507287,0.09491512,0.006653733,0.04176244,0.0005653417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004729302,0.004117284,0.9929036,0.0007921364,0.00104452,0.00057769,0.000008743421,0.00005516116,0.00002786756],"genre_scores_gemma":[0.1182363,0.0001351217,0.8806407,0.0002393153,0.0005644623,0.00001939549,0.000004329564,0.00003290656,0.0001275407],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8404851,"threshold_uncertainty_score":0.999883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00996440083812439,"score_gpt":0.2512072407552337,"score_spread":0.2412428399171093,"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."}}