{"id":"https://openalex.org/W4415648063","doi":"https://doi.org/10.3390/computers14110459","title":"Efficient Image Restoration for Autonomous Vehicles and Traffic Systems: A Knowledge Distillation Approach to Enhancing Environmental Perception","display_name":"Efficient Image Restoration for Autonomous Vehicles and Traffic Systems: A Knowledge Distillation Approach to Enhancing Environmental Perception","publication_year":2025,"publication_date":"2025-10-24","ids":{"openalex":"https://openalex.org/W4415648063","doi":"https://doi.org/10.3390/computers14110459"},"language":"en","primary_location":{"id":"doi:10.3390/computers14110459","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14110459","pdf_url":null,"source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/computers14110459","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055478053","display_name":"Yongheng Zhang","orcid":"https://orcid.org/0000-0002-5953-1215"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongheng Zhang","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications (BUPT), No. 10 Xitucheng Road, Haidian District, Beijing 100876, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications (BUPT), No. 10 Xitucheng Road, Haidian District, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5055478053"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33290897,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"11","first_page":"459","last_page":"459"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.5981000065803528,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.5981000065803528,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.1500999927520752,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.06759999692440033,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/software-deployment","display_name":"Software deployment","score":0.532800018787384},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5281000137329102},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.49880000948905945},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4059000015258789},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.40470001101493835},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3968000113964081},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3799999952316284},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.35670000314712524}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5967000126838684},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.532800018787384},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5281000137329102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5098999738693237},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.49880000948905945},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4059000015258789},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.40470001101493835},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3968000113964081},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.35670000314712524},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34299999475479126},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32100000977516174},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.296999990940094},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26980000734329224},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.25940001010894775},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2556999921798706},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2556000053882599}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/computers14110459","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14110459","pdf_url":null,"source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7563bab325484d3dba14c0a178a77c24","is_oa":true,"landing_page_url":"https://doaj.org/article/7563bab325484d3dba14c0a178a77c24","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computers, Vol 14, Iss 11, p 459 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/computers14110459","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14110459","pdf_url":null,"source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1982471090","https://openalex.org/W2028763589","https://openalex.org/W2030108224","https://openalex.org/W2083610878","https://openalex.org/W2103913786","https://openalex.org/W2114770744","https://openalex.org/W2133665775","https://openalex.org/W2147318913","https://openalex.org/W2206123561","https://openalex.org/W2466666260","https://openalex.org/W2467473805","https://openalex.org/W2474628748","https://openalex.org/W2560533888","https://openalex.org/W2740982616","https://openalex.org/W2748263833","https://openalex.org/W2901505625","https://openalex.org/W2912435603","https://openalex.org/W2930755307","https://openalex.org/W2952787292","https://openalex.org/W2959289524","https://openalex.org/W2963928582","https://openalex.org/W2964005298","https://openalex.org/W2964212750","https://openalex.org/W2965217508","https://openalex.org/W2997563695","https://openalex.org/W3007063652","https://openalex.org/W3034278302","https://openalex.org/W3034331889","https://openalex.org/W3035250394","https://openalex.org/W3035631962","https://openalex.org/W3085824656","https://openalex.org/W3107405705","https://openalex.org/W3170697543","https://openalex.org/W3173269149","https://openalex.org/W3177378457","https://openalex.org/W3177640626","https://openalex.org/W3180034634","https://openalex.org/W3201952986","https://openalex.org/W3207918547","https://openalex.org/W4221166948","https://openalex.org/W4221167590","https://openalex.org/W4225672218","https://openalex.org/W4285345657","https://openalex.org/W4312295033","https://openalex.org/W4312399981","https://openalex.org/W4312452088","https://openalex.org/W4312812783","https://openalex.org/W4312880823","https://openalex.org/W4327808545","https://openalex.org/W4378189200","https://openalex.org/W4386072291","https://openalex.org/W4386075800","https://openalex.org/W4386076209","https://openalex.org/W4386170296","https://openalex.org/W4408345706"],"related_works":[],"abstract_inverted_index":{"Image":[0],"restoration":[1,74],"tasks":[2,24,168],"such":[3],"as":[4,136,142],"deraining,":[5],"deblurring,":[6],"and":[7,19,30,108,138,163,183],"dehazing":[8],"are":[9],"crucial":[10],"for":[11,23,67,115,186],"enhancing":[12,166],"the":[13,121,129,133,139,147,194],"environmental":[14],"perception":[15],"of":[16,123,175,196],"autonomous":[17,191],"vehicles":[18],"traffic":[20],"systems,":[21,192],"particularly":[22],"like":[25,169],"vehicle":[26],"detection,":[27],"pedestrian":[28],"detection":[29],"lane":[31],"line":[32],"identification.":[33],"While":[34],"transformer-based":[35],"models":[36],"excel":[37],"in":[38,179,190],"these":[39],"tasks,":[40],"their":[41],"prohibitive":[42],"computational":[43],"complexity":[44],"hinders":[45],"real-world":[46],"deployment":[47],"on":[48],"resource-constrained":[49],"platforms.":[50],"To":[51],"bridge":[52],"this":[53,55,176],"gap,":[54],"paper":[56],"introduces":[57],"a":[58,84,91,101,124,158,181],"novel":[59],"Soft":[60],"Knowledge":[61],"Distillation":[62],"(SKD)":[63],"framework,":[64],"designed":[65],"specifically":[66],"creating":[68],"highly":[69],"efficient":[70,197],"yet":[71],"powerful":[72],"image":[73],"models.":[75],"Our":[76],"core":[77],"innovation":[78],"is":[79],"twofold:":[80],"first,":[81],"we":[82,119],"propose":[83],"Multi-dimensional":[85],"Cross-Net":[86],"Attention(MCA)":[87],"mechanism":[88],"that":[89,154],"allows":[90],"compact":[92],"student":[93],"model":[94,104,198],"to":[95],"learn":[96],"comprehensive":[97],"attention":[98],"relationships":[99],"from":[100],"large":[102],"teacher":[103],"across":[105],"both":[106],"spatial":[107],"channel":[109],"dimensions,":[110],"capturing":[111],"fine-grained":[112],"details":[113],"essential":[114],"high-quality":[116],"restoration.":[117],"Second,":[118],"pioneer":[120],"use":[122],"contrastive":[125],"learning":[126],"loss":[127],"at":[128],"reconstruction":[130,149],"level,":[131],"treating":[132],"teacher\u2019s":[134],"outputs":[135],"positives":[137],"degraded":[140],"inputs":[141],"negatives,":[143],"which":[144],"significantly":[145],"elevates":[146],"student\u2019s":[148],"quality.":[150],"Extensive":[151],"experiments":[152],"demonstrate":[153],"our":[155],"method":[156],"achieves":[157],"superior":[159],"trade-off":[160],"between":[161],"performance":[162],"efficiency,":[164],"notably":[165],"downstream":[167],"object":[170],"detection.":[171],"The":[172],"primary":[173],"contributions":[174],"work":[177],"lie":[178],"delivering":[180],"practical":[182],"compelling":[184],"solution":[185],"real-time":[187],"perceptual":[188],"enhancement":[189],"pushing":[193],"boundaries":[195],"design.":[199]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-29T00:00:00"}