{"id":"https://openalex.org/W2774078898","doi":"https://doi.org/10.1109/mfi.2017.8170444","title":"Light-weight semantic segmentation for compound images","display_name":"Light-weight semantic segmentation for compound images","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2774078898","doi":"https://doi.org/10.1109/mfi.2017.8170444","mag":"2774078898"},"language":"en","primary_location":{"id":"doi:10.1109/mfi.2017.8170444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2017.8170444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","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/A5051789113","display_name":"Geonho Cha","orcid":"https://orcid.org/0000-0002-3008-4642"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Geonho Cha","raw_affiliation_strings":["Department of Electrical and Computer Engineering and ASRI, Seoul National University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and ASRI, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075799441","display_name":"Hwiyeon Yoo","orcid":"https://orcid.org/0000-0002-3331-3172"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hwiyeon Yoo","raw_affiliation_strings":["Department of Electrical and Computer Engineering and ASRI, Seoul National University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and ASRI, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422970","display_name":"Dong\u2010Hoon Lee","orcid":"https://orcid.org/0000-0002-5013-4440"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Donghoon Lee","raw_affiliation_strings":["Department of Electrical and Computer Engineering and ASRI, Seoul National University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and ASRI, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033764106","display_name":"Songhwai Oh","orcid":"https://orcid.org/0000-0002-9781-2018"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Songhwai Oh","raw_affiliation_strings":["Department of Electrical and Computer Engineering and ASRI, Seoul National University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering and ASRI, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5051789113"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":0.2354,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63476149,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"295","last_page":"300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9995999932289124,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9975000023841858,"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/T11408","display_name":"Advanced Optical Imaging Technologies","score":0.9961000084877014,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compound-eye","display_name":"Compound eye","score":0.8613237738609314},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.739061713218689},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.737589955329895},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7333712577819824},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.710484504699707},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5885381102561951},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5563995838165283},{"id":"https://openalex.org/keywords/lens","display_name":"Lens (geology)","score":0.4908660054206848},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4777457118034363},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4252853989601135},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.12075686454772949},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11151006817817688},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06934890151023865}],"concepts":[{"id":"https://openalex.org/C2909722775","wikidata":"https://www.wikidata.org/wiki/Q942537","display_name":"Compound eye","level":2,"score":0.8613237738609314},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.739061713218689},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.737589955329895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7333712577819824},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.710484504699707},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5885381102561951},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5563995838165283},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.4908660054206848},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4777457118034363},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4252853989601135},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.12075686454772949},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11151006817817688},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06934890151023865},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mfi.2017.8170444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2017.8170444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323103","display_name":"Agency for Defense Development","ror":"https://ror.org/05fhe0r85"},{"id":"https://openalex.org/F4320334874","display_name":"Defense Acquisition Program Administration","ror":"https://ror.org/04bjg9m96"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1502510213","https://openalex.org/W1578197944","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W1987687683","https://openalex.org/W1992723124","https://openalex.org/W2015206113","https://openalex.org/W2054279472","https://openalex.org/W2077696274","https://openalex.org/W2113165521","https://openalex.org/W2116951336","https://openalex.org/W2147880316","https://openalex.org/W2163609611","https://openalex.org/W2165409871","https://openalex.org/W2194775991","https://openalex.org/W2282078336","https://openalex.org/W2412782625","https://openalex.org/W2545985378","https://openalex.org/W2561196672","https://openalex.org/W4285719527","https://openalex.org/W6634886587","https://openalex.org/W6639102338","https://openalex.org/W6682082992","https://openalex.org/W6695776777","https://openalex.org/W6715287400"],"related_works":["https://openalex.org/W2389821416","https://openalex.org/W2025150795","https://openalex.org/W4293226380","https://openalex.org/W2043669449","https://openalex.org/W1432272220","https://openalex.org/W649534374","https://openalex.org/W2086483225","https://openalex.org/W3183232947","https://openalex.org/W1187505509","https://openalex.org/W4321487865"],"abstract_inverted_index":{"The":[0,81,152],"eye":[1,41,47,124],"structure":[2,48],"of":[3,19,33,49,67,89,122],"insects,":[4,50],"which":[5,43,126],"is":[6,127,150],"called":[7],"a":[8,16,39,68,84,111,135,146],"compound":[9,40,46,51,69,79,104,112,123,142,157],"eye,":[10],"has":[11,15,83],"interesting":[12,55],"advantages.":[13],"It":[14],"large":[17],"field":[18],"view,":[20],"low":[21,73,136],"aberrations,":[22],"compact":[23],"size,":[24],"short":[25],"image":[26],"processing":[27],"time,":[28],"and":[29,72,87],"an":[30],"infinite":[31],"depth":[32],"field.":[34],"If":[35],"we":[36,63,117],"can":[37,57,118],"design":[38,66],"camera":[42,70,94,99],"mimics":[44],"the":[45,65],"images":[52,105,143,158],"with":[53],"these":[54],"advantages":[56],"be":[58],"obtained.":[59],"In":[60,114],"this":[61,115],"paper,":[62],"consider":[64],"prototype":[71,82],"complexity":[74,137],"semantic":[75,138,163],"segmentation":[76,139,164],"scheme":[77,140],"for":[78,129,141,162],"images.":[80,168],"hemisphere":[85],"shape":[86],"consists":[88],"several":[90],"synchronized":[91],"single-lens":[92],"reflex":[93],"modules.":[95],"Images":[96],"captured":[97],"from":[98],"modules":[100],"are":[101,159],"mapped":[102],"to":[103,109],"using":[106],"multi-view":[107],"geometry":[108],"emulate":[110],"eye.":[113],"way,":[116],"simulate":[119],"various":[120],"configurations":[121],"structures,":[125],"useful":[128],"developing":[130],"high-level":[131],"applications.":[132],"After":[133],"that,":[134],"based":[144],"on":[145],"convolutional":[147],"neural":[148],"network":[149],"proposed.":[151],"experimental":[153],"result":[154],"shows":[155],"that":[156],"more":[160],"suitable":[161],"than":[165],"typical":[166],"RGB":[167]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}