{"id":"https://openalex.org/W3187493240","doi":"https://doi.org/10.1109/iros51168.2021.9636620","title":"Memory-based Semantic Segmentation for Off-road Unstructured Natural Environments","display_name":"Memory-based Semantic Segmentation for Off-road Unstructured Natural Environments","publication_year":2021,"publication_date":"2021-09-27","ids":{"openalex":"https://openalex.org/W3187493240","doi":"https://doi.org/10.1109/iros51168.2021.9636620","mag":"3187493240"},"language":"en","primary_location":{"id":"doi:10.1109/iros51168.2021.9636620","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9636620","pdf_url":null,"source":{"id":"https://openalex.org/S4363607734","display_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5049665125","display_name":"Youngsaeng Jin","orcid":"https://orcid.org/0000-0002-5289-4419"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Youngsaeng Jin","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102000970","display_name":"David K. Han","orcid":"https://orcid.org/0000-0001-5055-5408"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Han","raw_affiliation_strings":["Electrical and Computer Engineering, Drexel University, Philadelphia, PA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Drexel University, Philadelphia, PA","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026204977","display_name":"Hanseok Ko","orcid":"https://orcid.org/0000-0002-8744-4514"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hanseok Ko","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049665125"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":0.7188,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.81365207,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"24","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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":0.9991999864578247,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.8484176993370056},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6882603168487549},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6072015166282654},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5336208343505859},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5219623446464539},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5168867111206055},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5114216208457947}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8484176993370056},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6882603168487549},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6072015166282654},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5336208343505859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5219623446464539},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5168867111206055},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5114216208457947},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros51168.2021.9636620","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9636620","pdf_url":null,"source":{"id":"https://openalex.org/S4363607734","display_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4000000059604645,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1745334888","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1913356549","https://openalex.org/W2106053110","https://openalex.org/W2108598243","https://openalex.org/W2115579991","https://openalex.org/W2125215748","https://openalex.org/W2133564696","https://openalex.org/W2157331557","https://openalex.org/W2188119724","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2472819217","https://openalex.org/W2473131906","https://openalex.org/W2507296351","https://openalex.org/W2549139847","https://openalex.org/W2560023338","https://openalex.org/W2607579284","https://openalex.org/W2630837129","https://openalex.org/W2775127214","https://openalex.org/W2798791840","https://openalex.org/W2799213142","https://openalex.org/W2799217622","https://openalex.org/W2890782586","https://openalex.org/W2892220819","https://openalex.org/W2892614179","https://openalex.org/W2895340641","https://openalex.org/W2949341804","https://openalex.org/W2950527759","https://openalex.org/W2953044442","https://openalex.org/W2955058313","https://openalex.org/W2962802951","https://openalex.org/W2962850830","https://openalex.org/W2963163009","https://openalex.org/W2963727650","https://openalex.org/W2963840672","https://openalex.org/W2964308564","https://openalex.org/W2964309882","https://openalex.org/W2964312929","https://openalex.org/W2969825080","https://openalex.org/W2981689412","https://openalex.org/W2981899103","https://openalex.org/W2991471181","https://openalex.org/W2997564896","https://openalex.org/W3000570262","https://openalex.org/W3003922739","https://openalex.org/W3014641072","https://openalex.org/W3035240825","https://openalex.org/W3109808990","https://openalex.org/W3157525179","https://openalex.org/W3169887922","https://openalex.org/W3206164009","https://openalex.org/W4303633609","https://openalex.org/W6630875275","https://openalex.org/W6639824700","https://openalex.org/W6675751002","https://openalex.org/W6679434410","https://openalex.org/W6684821475","https://openalex.org/W6687029160","https://openalex.org/W6696085341","https://openalex.org/W6720057410","https://openalex.org/W6724670942","https://openalex.org/W6729342207","https://openalex.org/W6732703391","https://openalex.org/W6736760071","https://openalex.org/W6739696289","https://openalex.org/W6746904271","https://openalex.org/W6748481559","https://openalex.org/W6750703173","https://openalex.org/W6754852571","https://openalex.org/W6756709046","https://openalex.org/W6765590276","https://openalex.org/W6767071366","https://openalex.org/W6786342384"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"With":[0],"the":[1,88,94,106,144,168,190,195,221],"availability":[2],"of":[3,79,105,143,162,197],"many":[4],"datasets":[5],"tailored":[6],"for":[7,16,26,64,235],"autonomous":[8,238],"driving":[9,18],"in":[10,41,50,115,134,139,159],"real-world":[11],"urban":[12,17],"scenes,":[13],"semantic":[14,24,65],"segmentation":[15,25,37,66,121,199],"scenes":[19,212],"achieves":[20],"significant":[21,77,113],"progress.":[22],"However,":[23],"off-road,":[27,182,209],"unstructured":[28,183,210],"environments":[29],"is":[30,67,98,132,151],"not":[31],"widely":[32],"studied.":[33],"Directly":[34],"applying":[35],"existing":[36,198],"networks":[38,122,200],"often":[39],"results":[40,187],"performance":[42,196],"degradation":[43],"as":[44,54,82],"they":[45],"cannot":[46],"overcome":[47,70],"intrinsic":[48],"problems":[49],"such":[51,53],"environments,":[52],"illumination":[55,127],"changes.":[56,128],"In":[57,85],"this":[58],"paper,":[59],"a":[60,160,232],"built-in":[61],"memory":[62,74,83,96,145,149,192],"module":[63,75,97,150,193],"proposed":[68,95,148,191,222],"to":[69,87,101,136,203],"these":[71],"problems.":[72],"The":[73,147],"stores":[76],"representations":[78,142],"training":[80,135],"images":[81],"items.":[84],"addition":[86],"encoder":[89],"embedding":[90],"like":[91],"items":[92],"together,":[93],"specifically":[99],"designed":[100],"cluster":[102],"together":[103],"instances":[104],"same":[107],"class":[108],"even":[109],"when":[110],"there":[111],"are":[112,179],"variances":[114],"embedded":[116],"features.":[117],"Therefore,":[118],"it":[119,155,230],"makes":[120],"better":[123],"deal":[124],"with":[125,213],"unexpected":[126],"A":[129],"triplet":[130],"loss":[131],"used":[133],"minimize":[137],"redundancy":[138],"storing":[140],"discriminative":[141],"module.":[146],"general":[152],"so":[153],"that":[154,189],"can":[156,224],"be":[157,225],"adopted":[158],"variety":[161],"networks.":[163],"We":[164],"conduct":[165],"experiments":[166],"on":[167],"Robot":[169],"Unstructured":[170],"Ground":[171],"Driving":[172],"(RUGD)":[173],"dataset":[174],"and":[175,201,217],"RELLIS":[176],"dataset,":[177],"which":[178],"collected":[180],"from":[181],"natural":[184,211],"environments.":[185],"Experimental":[186],"show":[188],"improves":[194],"contributes":[202],"capturing":[204],"unclear":[205],"objects":[206],"over":[207],"various":[208],"equivalent":[214],"computational":[215],"cost":[216],"network":[218],"parameters.":[219],"As":[220],"method":[223],"integrated":[226],"into":[227],"compact":[228],"networks,":[229],"presents":[231],"viable":[233],"approach":[234],"resource-limited":[236],"small":[237],"platforms.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}