{"id":"https://openalex.org/W4375869402","doi":"https://doi.org/10.1109/icassp49357.2023.10097079","title":"Frequency and Scale Perspectives of Feature Extraction","display_name":"Frequency and Scale Perspectives of Feature Extraction","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4375869402","doi":"https://doi.org/10.1109/icassp49357.2023.10097079"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10097079","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10097079","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036779666","display_name":"Liangqi Zhang","orcid":"https://orcid.org/0000-0003-0782-4849"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangqi Zhang","raw_affiliation_strings":["Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037851804","display_name":"Yihao Luo","orcid":"https://orcid.org/0000-0001-5525-3687"},"institutions":[{"id":"https://openalex.org/I4210109015","display_name":"Analysis and Testing Centre","ror":"https://ror.org/01m9scr97","country_code":"CN","type":"facility","lineage":["https://openalex.org/I107851509","https://openalex.org/I4210109015","https://openalex.org/I4210127390","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihao Luo","raw_affiliation_strings":["Yichang Testing Technique Research Institute","Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yichang Testing Technique Research Institute","institution_ids":["https://openalex.org/I4210109015"]},{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002534392","display_name":"Xiang Cao","orcid":"https://orcid.org/0000-0002-8813-9669"},"institutions":[{"id":"https://openalex.org/I198357462","display_name":"Changsha University","ror":"https://ror.org/011d8sm39","country_code":"CN","type":"education","lineage":["https://openalex.org/I198357462"]},{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Cao","raw_affiliation_strings":["Changsha University","Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changsha University","institution_ids":["https://openalex.org/I198357462"]},{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055167423","display_name":"Haibo Shen","orcid":"https://orcid.org/0000-0002-1183-6570"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haibo Shen","raw_affiliation_strings":["Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056778408","display_name":"Tianjiang Wang","orcid":"https://orcid.org/0000-0002-8664-4143"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianjiang Wang","raw_affiliation_strings":["Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7047178745269775},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.685291051864624},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6801999807357788},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6743248701095581},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6241565942764282},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5561724305152893},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5280538201332092},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5194094181060791},{"id":"https://openalex.org/keywords/scale-space","display_name":"Scale space","score":0.4522725045681},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4451761841773987}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7047178745269775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.685291051864624},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6801999807357788},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6743248701095581},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6241565942764282},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5561724305152893},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5280538201332092},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5194094181060791},{"id":"https://openalex.org/C99102927","wikidata":"https://www.wikidata.org/wiki/Q3058184","display_name":"Scale space","level":4,"score":0.4522725045681},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4451761841773987},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10097079","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10097079","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1549358575","https://openalex.org/W1673923490","https://openalex.org/W1825675169","https://openalex.org/W1849277567","https://openalex.org/W1945616565","https://openalex.org/W2022735534","https://openalex.org/W2042243448","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2949582403","https://openalex.org/W2982083293","https://openalex.org/W2994720379","https://openalex.org/W3034175346","https://openalex.org/W3094502228","https://openalex.org/W3118608800","https://openalex.org/W3138516171","https://openalex.org/W4239072543","https://openalex.org/W4293861706","https://openalex.org/W4297775537","https://openalex.org/W6677995690","https://openalex.org/W6684191040","https://openalex.org/W6685133223","https://openalex.org/W6762718338","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W4399188509","https://openalex.org/W2318112981","https://openalex.org/W4210874298"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,28,37,72],"networks":[2,29,38,73,138],"(CNNs)":[3],"have":[4,41],"achieved":[5],"superior":[6],"performance":[7],"but":[8,46],"still":[9],"lack":[10],"clarity":[11],"about":[12],"the":[13,25,56,61,69,76],"nature":[14],"and":[15,32,43,55,84,106],"properties":[16],"of":[17,27,58,123],"feature":[18,112],"extraction.":[19],"In":[20],"this":[21,88],"paper,":[22],"by":[23,102],"analyzing":[24],"sensitivity":[26],"to":[30,68,78,115,132],"frequencies":[31],"scales,":[33],"we":[34,90],"find":[35],"that":[36,71],"not":[39],"only":[40],"low-":[42],"mediumfrequency":[44],"biases":[45],"also":[47],"prefer":[48],"different":[49,53,127],"frequency":[50,63],"bands":[51],"for":[52],"classes,":[54],"scale":[57,104],"objects":[59],"influences":[60],"preferred":[62],"bands.":[64],"These":[65],"observations":[66],"lead":[67],"hypothesis":[70],"must":[74],"learn":[75],"ability":[77],"extract":[79],"features":[80,101,125],"at":[81],"various":[82,140],"scales":[83,128],"frequencies.":[85],"To":[86],"corroborate":[87],"hypothesis,":[89],"propose":[91],"a":[92],"network":[93],"architecture":[94],"based":[95],"on":[96,139],"Gaussian":[97],"derivatives,":[98],"which":[99],"extracts":[100],"constructing":[103],"space":[105],"employing":[107],"partial":[108],"derivatives":[109],"as":[110],"local":[111],"extraction":[113],"operators":[114],"separate":[116],"high-frequency":[117],"information.":[118],"This":[119],"manually":[120],"designed":[121],"method":[122],"extracting":[124],"from":[126],"allows":[129],"our":[130],"GSSDNets":[131],"achieve":[133],"comparable":[134],"accuracy":[135],"with":[136],"vanilla":[137],"datasets.":[141]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
