{"id":"https://openalex.org/W3027915297","doi":"https://doi.org/10.1109/isbi45749.2020.9098527","title":"A Multi-Task Self-Supervised Learning Framework for Scopy Images","display_name":"A Multi-Task Self-Supervised Learning Framework for Scopy Images","publication_year":2020,"publication_date":"2020-04-01","ids":{"openalex":"https://openalex.org/W3027915297","doi":"https://doi.org/10.1109/isbi45749.2020.9098527","mag":"3027915297"},"language":"en","primary_location":{"id":"doi:10.1109/isbi45749.2020.9098527","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi45749.2020.9098527","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","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/A5101710180","display_name":"Yuexiang Li","orcid":"https://orcid.org/0000-0001-8076-2619"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuexiang Li","raw_affiliation_strings":["YouTu Lab, Tencent, Shenzhen, China","Youtu Lab, Tencent,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"YouTu Lab, Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Youtu Lab, Tencent,Shenzhen,China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100362822","display_name":"Jiawei Chen","orcid":"https://orcid.org/0000-0002-8195-1582"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Chen","raw_affiliation_strings":["YouTu Lab, Tencent, Shenzhen, China","Youtu Lab, Tencent,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"YouTu Lab, Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Youtu Lab, Tencent,Shenzhen,China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051649145","display_name":"Yefeng Zheng","orcid":"https://orcid.org/0000-0003-2195-2847"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yefeng Zheng","raw_affiliation_strings":["YouTu Lab, Tencent, Shenzhen, China","Youtu Lab, Tencent,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"YouTu Lab, Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Youtu Lab, Tencent,Shenzhen,China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101710180"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":1.0747,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.79436378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2005","last_page":"2009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9958999752998352,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9958999752998352,"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/T10862","display_name":"AI in cancer detection","score":0.995199978351593,"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"}},{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9865000247955322,"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":0.8266013860702515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7081550359725952},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5728198289871216},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5407093167304993},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5283328294754028},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.458121657371521},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4230262041091919},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4213283658027649}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8266013860702515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7081550359725952},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5728198289871216},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5407093167304993},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5283328294754028},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.458121657371521},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4230262041091919},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4213283658027649},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/isbi45749.2020.9098527","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi45749.2020.9098527","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2194775991","https://openalex.org/W2308529009","https://openalex.org/W2326925005","https://openalex.org/W2412782625","https://openalex.org/W2581082771","https://openalex.org/W2628684354","https://openalex.org/W2808604288","https://openalex.org/W2962824366","https://openalex.org/W2963946669","https://openalex.org/W6639824700","https://openalex.org/W6698507324","https://openalex.org/W6701655646","https://openalex.org/W6846221585"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W4315434538","https://openalex.org/W4380075502"],"abstract_inverted_index":{"The":[0,74],"training":[1,10,72],"of":[2,9,16,25,71,97,100],"deep":[3,37],"learning":[4,38,49],"models":[5],"requires":[6],"large":[7],"amount":[8],"data.":[11,73],"However,":[12],"as":[13],"the":[14,23,36,54,60,69,98,105],"annotations":[15],"medical":[17,27],"data":[18,66],"are":[19,93],"difficult":[20],"to":[21,33,85,104,114],"acquire,":[22],"quantity":[24],"annotated":[26],"images":[28],"is":[29],"often":[30],"not":[31],"enough":[32],"well":[34],"train":[35],"networks.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43],"propose":[44],"a":[45,115],"novel":[46],"multi-task":[47],"self-supervised":[48],"framework,":[50],"namely":[51],"ColorMe,":[52],"for":[53],"scopy":[55,101],"images,":[56],"which":[57,92],"deeply":[58],"exploits":[59],"rich":[61],"information":[62],"embedded":[63],"in":[64,95],"raw":[65],"and":[67,88,125],"looses":[68],"demand":[70],"approach":[75],"pre-trains":[76],"neural":[77],"networks":[78,112],"on":[79,118],"multiple":[80],"proxy":[81],"tasks,":[82],"i.e.,":[83],"green":[84],"red/blue":[86],"colorization":[87],"color":[89],"distribution":[90],"estimation,":[91],"defined":[94],"terms":[96],"prior-knowledge":[99],"images.":[102],"Compared":[103],"train-from-scratch":[106],"strategy,":[107],"fine-tuning":[108],"from":[109],"these":[110],"pre-trained":[111],"leads":[113],"better":[116],"accuracy":[117],"various":[119],"tasks":[120],"-":[121],"cervix":[122],"type":[123],"classification":[124],"skin":[126],"lesion":[127],"segmentation.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
