{"id":"https://openalex.org/W2978996239","doi":"https://doi.org/10.1109/ijcnn.2019.8852149","title":"DeepSqueezeNet-CRF: A Lightweight Deep Model for Semantic Image Segmentation","display_name":"DeepSqueezeNet-CRF: A Lightweight Deep Model for Semantic Image Segmentation","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978996239","doi":"https://doi.org/10.1109/ijcnn.2019.8852149","mag":"2978996239"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5027610251","display_name":"Danyu Lai","orcid":"https://orcid.org/0000-0003-1946-5206"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Danyu Lai","raw_affiliation_strings":["School of Data Science and Computer, Sun Yat-sen University, GuangZhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Computer, Sun Yat-sen University, GuangZhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025168047","display_name":"Yique Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yique Deng","raw_affiliation_strings":["School of Data Science and Computer, Sun Yat-sen University, GuangZhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Computer, Sun Yat-sen University, GuangZhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100336450","display_name":"Long Chen","orcid":"https://orcid.org/0000-0003-4925-0572"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Chen","raw_affiliation_strings":["School of Data Science and Computer, Sun Yat-sen University, GuangZhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Computer, Sun Yat-sen University, GuangZhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027610251"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.5061,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.69557856,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval 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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7544580698013306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6326379776000977},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5925572514533997},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5559633374214172},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4926045536994934},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43354251980781555},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4200184643268585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7544580698013306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6326379776000977},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5925572514533997},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5559633374214172},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4926045536994934},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43354251980781555},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4200184643268585}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W78159342","https://openalex.org/W360623563","https://openalex.org/W1507506748","https://openalex.org/W1536680647","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1923115158","https://openalex.org/W1938976761","https://openalex.org/W1948751323","https://openalex.org/W1991367009","https://openalex.org/W2022508996","https://openalex.org/W2037227137","https://openalex.org/W2046382188","https://openalex.org/W2054279472","https://openalex.org/W2070724998","https://openalex.org/W2088049833","https://openalex.org/W2100588357","https://openalex.org/W2102605133","https://openalex.org/W2129259959","https://openalex.org/W2161236525","https://openalex.org/W2279098554","https://openalex.org/W2412320034","https://openalex.org/W2412644588","https://openalex.org/W2535516436","https://openalex.org/W2545985378","https://openalex.org/W2604724028","https://openalex.org/W2604970008","https://openalex.org/W2767899698","https://openalex.org/W2796419292","https://openalex.org/W2905361570","https://openalex.org/W2952793010","https://openalex.org/W6612134913","https://openalex.org/W6631782140"],"related_works":["https://openalex.org/W1669643531","https://openalex.org/W2122581818","https://openalex.org/W1631910785","https://openalex.org/W2159066190","https://openalex.org/W2739874619","https://openalex.org/W2110230079","https://openalex.org/W2117933325","https://openalex.org/W2117664411","https://openalex.org/W1721780360","https://openalex.org/W1507266234"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1,73],"neural":[2,31],"networks":[3],"(DCNNs)":[4],"has":[5],"shown":[6],"the":[7,16,45,64,67,91,102,105,130,148,159],"powerful":[8],"capability":[9],"in":[10],"image":[11,34],"semantic":[12,35],"segmentation,":[13],"along":[14],"with":[15,37,109,138,163],"huge":[17],"model":[18,42,59,85,153],"sizes":[19],"and":[20,40,87,122,132,155],"massive":[21],"parameters.":[22],"Our":[23,79],"key":[24],"insight":[25],"is":[26],"to":[27,66,116],"build":[28],"a":[29,56,110],"new":[30],"network":[32,151],"for":[33],"segmentation":[36],"fewer":[38,82],"parameters":[39],"smaller":[41,84],"size":[43,86,154],"under":[44],"premise":[46],"of":[47,72,134,150,158],"maintaining":[48],"state-of-the-art":[49,141],"performance.":[50,166],"In":[51],"this":[52],"paper,":[53],"we":[54,97],"propose":[55,98],"lightweight":[57],"deep":[58],"named":[60],"DeepSqueezeNet,":[61],"which":[62],"introduces":[63],"SqueezeNet":[65],"fullyconvolutional":[68],"networks,":[69],"replacing":[70],"parts":[71],"layers":[74],"by":[75,100],"Fire":[76],"Module":[77],"layers.":[78],"DeepSqueezeNet":[80],"contains":[81],"parameters,":[83,152],"higher":[88],"accuracy":[89],"than":[90],"original":[92,160],"fully-convolutional":[93],"networks.":[94],"Further":[95],"more,":[96],"DeepSqueezeNet-CRF":[99],"combining":[101],"responses":[103],"at":[104],"final":[106],"DCNN":[107],"layer":[108],"fully-connected":[111,161],"Conditional":[112],"Random":[113],"Field":[114],"(CRF)":[115],"improve":[117],"localization":[118],"accuracy.":[119],"Both":[120],"quantitative":[121],"qualitative":[123],"results":[124],"on":[125],"PASAL":[126],"VOC":[127],"2012":[128],"demonstrate":[129],"priority":[131],"feasibility":[133],"our":[135,144],"methods,":[136],"comparing":[137],"several":[139],"other":[140],"methods.":[142],"Especially,":[143],"methods":[145],"can":[146],"reduce":[147],"number":[149],"training":[156],"time":[157],"network,":[162],"even":[164],"better":[165]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}