{"id":"https://openalex.org/W3092702582","doi":"https://doi.org/10.3390/s20205852","title":"Seeing Pedestrian in the Dark via Multi-Task Feature Fusing-Sharing Learning for Imaging Sensors","display_name":"Seeing Pedestrian in the Dark via Multi-Task Feature Fusing-Sharing Learning for Imaging Sensors","publication_year":2020,"publication_date":"2020-10-16","ids":{"openalex":"https://openalex.org/W3092702582","doi":"https://doi.org/10.3390/s20205852","mag":"3092702582","pmid":"https://pubmed.ncbi.nlm.nih.gov/33081153"},"language":"en","primary_location":{"id":"doi:10.3390/s20205852","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20205852","pdf_url":"https://www.mdpi.com/1424-8220/20/20/5852/pdf","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/20/5852/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016974436","display_name":"Yuanzhi Wang","orcid":"https://orcid.org/0000-0003-2594-2574"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanzhi Wang","raw_affiliation_strings":["Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430073, China"],"raw_orcid":"https://orcid.org/0000-0003-2594-2574","affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430073, China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089404454","display_name":"Tao L\u00fc","orcid":"https://orcid.org/0000-0001-8117-2012"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Lu","raw_affiliation_strings":["Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430073, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430073, China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375832","display_name":"Tao Zhang","orcid":"https://orcid.org/0000-0002-7192-5153"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Zhang","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing 100191, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001831755","display_name":"Yuntao Wu","orcid":"https://orcid.org/0000-0001-7911-4104"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuntao Wu","raw_affiliation_strings":["Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430073, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430073, China","institution_ids":["https://openalex.org/I91125648"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100375832"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":0.9616,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.75435081,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"20","issue":"20","first_page":"5852","last_page":"5852"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9990000128746033,"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/subnetwork","display_name":"Subnetwork","score":0.91746985912323},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.8226877450942993},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7935690879821777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7390872836112976},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5553010106086731},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5303999185562134},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5284573435783386},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.5053604245185852},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4861147403717041},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.47983524203300476},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4732409417629242},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.45103511214256287},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4476557672023773},{"id":"https://openalex.org/keywords/fusion-mechanism","display_name":"Fusion mechanism","score":0.4414656162261963},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43110886216163635},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4184448719024658},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.369636595249176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33325567841529846},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30125004053115845},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.21340027451515198},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1368945837020874}],"concepts":[{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.91746985912323},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.8226877450942993},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7935690879821777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7390872836112976},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5553010106086731},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5303999185562134},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5284573435783386},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.5053604245185852},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4861147403717041},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.47983524203300476},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4732409417629242},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.45103511214256287},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4476557672023773},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.4414656162261963},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43110886216163635},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4184448719024658},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.369636595249176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33325567841529846},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30125004053115845},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.21340027451515198},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1368945837020874},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C103038307","wikidata":"https://www.wikidata.org/wiki/Q6556360","display_name":"Lipid bilayer fusion","level":3,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s20205852","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20205852","pdf_url":"https://www.mdpi.com/1424-8220/20/20/5852/pdf","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:33081153","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33081153","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:6bd9f129739d4401b1e35c465a8d8873","is_oa":true,"landing_page_url":"https://doaj.org/article/6bd9f129739d4401b1e35c465a8d8873","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 20, Iss 20, p 5852 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/20/5852/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s20205852","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 20; Issue 20; Pages: 5852","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7588961","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7588961","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20205852","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20205852","pdf_url":"https://www.mdpi.com/1424-8220/20/20/5852/pdf","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1076515565","display_name":null,"funder_award_id":"91638301","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2968496289","display_name":"\u57fa\u4e8e\u5f20\u91cf\u4ee3\u6570\u53ca\u5b50\u7a7a\u95f4\u65b9\u6cd5\u7684\u591a\u7ef4\u6b63\u5f26\u4fe1\u53f7\u53c2\u6570\u4f30\u8ba1\u53ca\u5176\u5feb\u901f\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61771353","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3362017729","display_name":null,"funder_award_id":"2016YFB1200100","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3500309933","display_name":null,"funder_award_id":"61501413","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G41121228","display_name":null,"funder_award_id":"41501505","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6188665429","display_name":null,"funder_award_id":"2019AAA045","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6346682572","display_name":null,"funder_award_id":"61671332","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G675449760","display_name":null,"funder_award_id":"61502354, 91638301, 61501413, 61671332, 41501505","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7499339693","display_name":null,"funder_award_id":"61502354","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8049222334","display_name":null,"funder_award_id":"62072350","funder_id":"https://openalex.org/F4320325438","funder_display_name":"Wuhan Institute of Technology"},{"id":"https://openalex.org/G941251740","display_name":null,"funder_award_id":"62072350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325438","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3092702582.pdf","grobid_xml":"https://content.openalex.org/works/W3092702582.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1614862348","https://openalex.org/W2031454541","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2117130368","https://openalex.org/W2162741153","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2549139847","https://openalex.org/W2570343428","https://openalex.org/W2594507094","https://openalex.org/W2613718673","https://openalex.org/W2629538667","https://openalex.org/W2752782242","https://openalex.org/W2770947844","https://openalex.org/W2793888589","https://openalex.org/W2885291434","https://openalex.org/W2895258308","https://openalex.org/W2896540732","https://openalex.org/W2896681474","https://openalex.org/W2904835235","https://openalex.org/W2913340405","https://openalex.org/W2914633159","https://openalex.org/W2922509574","https://openalex.org/W2927933146","https://openalex.org/W2941889397","https://openalex.org/W2956891660","https://openalex.org/W2963404857","https://openalex.org/W2963446712","https://openalex.org/W2963877604","https://openalex.org/W2964081807","https://openalex.org/W2964247799","https://openalex.org/W3012573144","https://openalex.org/W3034704453","https://openalex.org/W3034752215","https://openalex.org/W3106250896","https://openalex.org/W6754146604"],"related_works":["https://openalex.org/W2237537322","https://openalex.org/W2950678851","https://openalex.org/W4301248618","https://openalex.org/W2472390602","https://openalex.org/W2810783540","https://openalex.org/W2165343651","https://openalex.org/W2343790552","https://openalex.org/W2242427765","https://openalex.org/W2075830955","https://openalex.org/W4309969809"],"abstract_inverted_index":{"Pedestrian":[0],"detection":[1,49,108,130,156,174],"is":[2,67],"an":[3,102],"essential":[4],"problem":[5],"of":[6,27,172],"computer":[7],"vision,":[8],"which":[9,34],"has":[10],"achieved":[11],"tremendous":[12],"success":[13],"under":[14],"controllable":[15],"conditions":[16],"using":[17,51],"visible":[18,180],"light":[19,181],"imaging":[20,182],"sensors":[21],"in":[22,38,58],"recent":[23],"years.":[24],"However,":[25],"most":[26,71],"them":[28],"do":[29],"not":[30],"consider":[31],"low-light":[32,59,123,176],"environments":[33],"are":[35],"very":[36],"common":[37],"real-world":[39],"applications.":[40],"In":[41],"this":[42,56],"paper,":[43],"we":[44],"propose":[45],"a":[46,84,93,106,111],"novel":[47,85],"pedestrian":[48,107,129,173],"algorithm":[50],"multi-task":[52,64,74,86,113,140],"learning":[53,65,75,87,115,142],"to":[54],"address":[55],"challenge":[57],"environments.":[60],"Specifically,":[61],"the":[62,70,122,128,138,163,170],"proposed":[63,97,164],"method":[66,88],"different":[68],"from":[69],"commonly":[72],"used":[73],"method-the":[76],"parameter":[77],"sharing":[78,94],"mechanism-in":[79],"deep":[80],"learning.":[81],"We":[82],"design":[83],"with":[89],"feature-level":[90,112,139],"fusion":[91,114,141],"and":[92,110,137,145,155,167],"mechanism.":[95],"The":[96,117],"approach":[98,165],"contains":[99],"three":[100],"parts:":[101],"image":[103,118,124,153],"relighting":[104,119,154],"subnetwork,":[105,109],"module.":[116],"subnetwork":[120,131],"adjusts":[121],"quality":[125],"for":[126,135,151],"detection,":[127],"learns":[132],"enhanced":[133],"features":[134,147],"prediction,":[136],"module":[143],"fuses":[144],"shares":[146],"among":[148],"component":[149],"networks":[150],"boosting":[152],"performance":[157,171],"simultaneously.":[158],"Experimental":[159],"results":[160],"show":[161],"that":[162],"consistently":[166],"significantly":[168],"improves":[169],"on":[175],"images":[177],"obtained":[178],"by":[179],"sensor.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}