{"id":"https://openalex.org/W4313001573","doi":"https://doi.org/10.1109/igarss46834.2022.9884727","title":"A Model Distillation Approach for Explaining Black-Box Models for Hyperspectral Image Classification","display_name":"A Model Distillation Approach for Explaining Black-Box Models for Hyperspectral Image Classification","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4313001573","doi":"https://doi.org/10.1109/igarss46834.2022.9884727"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9884727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884727","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","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/A5058660643","display_name":"G\u00fcl\u015fen Ta\u015fk\u0131n","orcid":"https://orcid.org/0000-0002-2294-4462"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Gulsen Taskin","raw_affiliation_strings":["Istanbul Technical University, Institute of Disaster Management,Istanbul,Turkey,34469"],"affiliations":[{"raw_affiliation_string":"Istanbul Technical University, Institute of Disaster Management,Istanbul,Turkey,34469","institution_ids":["https://openalex.org/I48912391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5058660643"],"corresponding_institution_ids":["https://openalex.org/I48912391"],"apc_list":null,"apc_paid":null,"fwci":1.4192,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82591662,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3592","last_page":"3595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9921000003814697,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.769179105758667},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7349462509155273},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.6828778386116028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6558889746665955},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6377438306808472},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5129997134208679},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.45950883626937866},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4592044949531555},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43767303228378296},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4200846552848816},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35004398226737976},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.342929482460022}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.769179105758667},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7349462509155273},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.6828778386116028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6558889746665955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6377438306808472},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5129997134208679},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.45950883626937866},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4592044949531555},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43767303228378296},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4200846552848816},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35004398226737976},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.342929482460022},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss46834.2022.9884727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884727","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:polen.itu.edu.tr:11527/66732","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/66732","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5099999904632568,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G4478428220","display_name":null,"funder_award_id":"MGA-2021-42793","funder_id":"https://openalex.org/F4320324489","funder_display_name":"Istanbul Teknik \u00dcniversitesi"}],"funders":[{"id":"https://openalex.org/F4320324489","display_name":"Istanbul Teknik \u00dcniversitesi","ror":"https://ror.org/059636586"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2049774453","https://openalex.org/W2106600817","https://openalex.org/W2321957512","https://openalex.org/W2764034829","https://openalex.org/W2782522152","https://openalex.org/W2887205128","https://openalex.org/W2889198848","https://openalex.org/W2891503716","https://openalex.org/W2913323966","https://openalex.org/W2921708311","https://openalex.org/W2921802966","https://openalex.org/W2945526235","https://openalex.org/W2945595726","https://openalex.org/W2962851944","https://openalex.org/W3012380364","https://openalex.org/W3130093949","https://openalex.org/W3130223471","https://openalex.org/W3133902755","https://openalex.org/W3140885850","https://openalex.org/W3146764839","https://openalex.org/W3173991935","https://openalex.org/W6685133223"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2027399350","https://openalex.org/W2060875994","https://openalex.org/W2044184146","https://openalex.org/W4377865163","https://openalex.org/W3184396788","https://openalex.org/W3029990846"],"abstract_inverted_index":{"Recent":[0],"studies":[1],"in":[2,27,87,98,123,177],"remote":[3,46,100],"sensing":[4,47,101],"reveal":[5],"that":[6,44,162],"complex":[7,170],"nonlinear":[8,171],"learning":[9,14,17,25,96,108],"models":[10,109,127],"such":[11,31,70,107],"as":[12,32],"deep":[13],"or":[15],"ensemble-based":[16],"are":[18,68,72,134],"mostly":[19],"preferred":[20],"compared":[21],"to":[22,114,144],"shallow":[23,94],"machine":[24,95],"methods":[26,71,81,97],"solving":[28],"many":[29,99],"problems":[30],"classification,":[33],"image":[34,179],"fusion,":[35],"change":[36],"detection,":[37],"unmixing,":[38],"and":[39,54,58,90,131],"object":[40],"recognition.":[41],"The":[42],"fact":[43],"much":[45],"data":[48],"can":[49,92,166],"be":[50],"obtained":[51],"quickly,":[52],"abundantly,":[53],"free":[55],"of":[56,63,77,119],"charge,":[57],"the":[59,75,120,163],"increasing":[60],"computing":[61],"power":[62],"computers":[64],"with":[65,149,173],"developing":[66],"technology,":[67],"why":[69,130],"preferred.":[73],"With":[74],"emergence":[76],"big":[78],"data,":[79],"these":[80,126],"provide":[82],"more":[83],"effective":[84],"solutions":[85],"than":[86],"past":[88],"years,":[89],"they":[91],"outperform":[93],"applications.":[102],"Despite":[103],"their":[104,115],"high":[105,121],"accuracy,":[106],"have":[110],"several":[111],"limitations":[112],"due":[113],"black-box":[116,147],"structure.":[117],"Because":[118],"nonlinearity":[122],"predictive":[124],"models,":[125],"cannot":[128],"explain":[129],"how":[132],"decisions":[133],"made.":[135],"This":[136],"paper":[137],"presents":[138],"a":[139,146,150,169,174],"global":[140],"model":[141,148,154,172],"distillation":[142],"approach":[143],"replace":[145,168],"fully":[151],"explainable":[152],"surrogate":[153],"utilizing":[155],"polynomial":[156],"chaos":[157],"expansion.":[158],"Preliminary":[159],"results":[160],"show":[161],"proposed":[164],"method":[165],"accurately":[167],"simpler":[175],"one":[176],"hyperspectral":[178],"classification.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}