{"id":"https://openalex.org/W3184761438","doi":"https://doi.org/10.1109/eit51626.2021.9491910","title":"Deep Learning optimization in remote sensing image segmentation using dilated convolutions and ShuffleNet","display_name":"Deep Learning optimization in remote sensing image segmentation using dilated convolutions and ShuffleNet","publication_year":2021,"publication_date":"2021-05-14","ids":{"openalex":"https://openalex.org/W3184761438","doi":"https://doi.org/10.1109/eit51626.2021.9491910","mag":"3184761438"},"language":"en","primary_location":{"id":"doi:10.1109/eit51626.2021.9491910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eit51626.2021.9491910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Electro Information Technology (EIT)","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/A5034845580","display_name":"Rahul Gomes","orcid":"https://orcid.org/0000-0002-5377-8196"},"institutions":[{"id":"https://openalex.org/I124727415","display_name":"University of Wisconsin\u2013Eau Claire","ror":"https://ror.org/03mnm0t94","country_code":"US","type":"education","lineage":["https://openalex.org/I124727415"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rahul Gomes","raw_affiliation_strings":["University of Wisconsin-Eau Claire,Dept. of Computer Science,Eau Claire,WI,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Eau Claire,Dept. of Computer Science,Eau Claire,WI,USA","institution_ids":["https://openalex.org/I124727415"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047996569","display_name":"Papia F. Rozario","orcid":"https://orcid.org/0000-0002-2066-9479"},"institutions":[{"id":"https://openalex.org/I124727415","display_name":"University of Wisconsin\u2013Eau Claire","ror":"https://ror.org/03mnm0t94","country_code":"US","type":"education","lineage":["https://openalex.org/I124727415"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Papia Rozario","raw_affiliation_strings":["University of Wisconsin-Eau Claire,Dept. of Geography and Anthropology,Eau Claire,WI,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Eau Claire,Dept. of Geography and Anthropology,Eau Claire,WI,USA","institution_ids":["https://openalex.org/I124727415"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010803825","display_name":"Nishan Adhikari","orcid":null},"institutions":[{"id":"https://openalex.org/I92063915","display_name":"Minot State University","ror":"https://ror.org/051j7cj03","country_code":"US","type":"education","lineage":["https://openalex.org/I92063915"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nishan Adhikari","raw_affiliation_strings":["Minot State University,Department of Math and Computer Science,Minot,ND,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Minot State University,Department of Math and Computer Science,Minot,ND,USA","institution_ids":["https://openalex.org/I92063915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2898,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.92693197,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"244","last_page":"249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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":0.7236858606338501},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5719045996665955},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5405222177505493},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5199909806251526},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5101564526557922},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.5086339712142944},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5001358985900879},{"id":"https://openalex.org/keywords/network-performance","display_name":"Network performance","score":0.43018779158592224},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4215097427368164},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33517125248908997},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.30343562364578247},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16304421424865723}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7236858606338501},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5719045996665955},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5405222177505493},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5199909806251526},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5101564526557922},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.5086339712142944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5001358985900879},{"id":"https://openalex.org/C203274722","wikidata":"https://www.wikidata.org/wiki/Q7001161","display_name":"Network performance","level":2,"score":0.43018779158592224},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4215097427368164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33517125248908997},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.30343562364578247},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16304421424865723},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eit51626.2021.9491910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eit51626.2021.9491910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Electro Information Technology (EIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W2014656852","https://openalex.org/W2084502283","https://openalex.org/W2092606759","https://openalex.org/W2097117768","https://openalex.org/W2131124296","https://openalex.org/W2150036648","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2291310586","https://openalex.org/W2359716859","https://openalex.org/W2515866431","https://openalex.org/W2516589589","https://openalex.org/W2531409750","https://openalex.org/W2557799930","https://openalex.org/W2599919765","https://openalex.org/W2610254470","https://openalex.org/W2619816672","https://openalex.org/W2630837129","https://openalex.org/W2774320778","https://openalex.org/W2891005358","https://openalex.org/W2899487481","https://openalex.org/W2908840642","https://openalex.org/W2911964244","https://openalex.org/W2914493539","https://openalex.org/W2950518324","https://openalex.org/W2962807143","https://openalex.org/W2963125010","https://openalex.org/W2963542991","https://openalex.org/W2963881378","https://openalex.org/W2964121744","https://openalex.org/W2972595414","https://openalex.org/W2972609722","https://openalex.org/W2996721521","https://openalex.org/W3007268491","https://openalex.org/W3105577662","https://openalex.org/W6629368666","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6639824700","https://openalex.org/W6684191040","https://openalex.org/W6696745930","https://openalex.org/W6728184133","https://openalex.org/W6739696289","https://openalex.org/W6740474667","https://openalex.org/W6759120840"],"related_works":["https://openalex.org/W2380853618","https://openalex.org/W2383090727","https://openalex.org/W4205478336","https://openalex.org/W2475532212","https://openalex.org/W2352416966","https://openalex.org/W4280540828","https://openalex.org/W2954340190","https://openalex.org/W1045279789","https://openalex.org/W4285188797","https://openalex.org/W4382721238"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1],"of":[2,45,70,83],"land":[3,5],"use":[4],"cover":[6],"data":[7],"using":[8],"deep":[9,22,86],"learning":[10,23,87],"networks":[11],"have":[12],"gained":[13],"significant":[14],"importance":[15],"in":[16,52,62,106],"the":[17,58,63,67,71,78,84,107,111],"remote":[18],"sensing":[19],"domain.":[20],"However,":[21],"architectures":[24,88,116],"are":[25,50],"computation-intensive.":[26],"In":[27],"this":[28],"research,":[29],"we":[30],"propose":[31],"an":[32],"Atrous":[33,60],"Shuffle-UNet":[34],"network,":[35],"which":[36,49],"is":[37],"designed":[38],"to":[39,81,113],"be":[40],"lightweight.":[41],"The":[42,103],"network":[43,55,65,72,80,112],"comprises":[44],"modified":[46],"ShuffleNet":[47,101,108],"units":[48,109],"arranged":[51],"a":[53,97],"similar":[54],"structure":[56],"as":[57,90],"UNet.":[59],"convolution":[61],"proposed":[64,79,104],"increases":[66],"receptive":[68],"field":[69],"enabling":[73],"faster":[74],"convergence.":[75],"We":[76],"compare":[77],"state":[82],"art":[85],"such":[89],"UNet,":[91],"UNet":[92,98],"with":[93,99,120],"ResNet":[94],"modules":[95],"and":[96,117],"standard":[100],"modules.":[102],"changes":[105],"enable":[110],"outperform":[114],"these":[115],"do":[118],"so":[119],"significantly":[121],"less":[122],"parameters.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}