{"id":"https://openalex.org/W4407874968","doi":"https://doi.org/10.3390/make7010022","title":"Automatic Prompt Generation Using Class Activation Maps for Foundational Models: A Polyp Segmentation Case Study","display_name":"Automatic Prompt Generation Using Class Activation Maps for Foundational Models: A Polyp Segmentation Case Study","publication_year":2025,"publication_date":"2025-02-24","ids":{"openalex":"https://openalex.org/W4407874968","doi":"https://doi.org/10.3390/make7010022"},"language":"en","primary_location":{"id":"doi:10.3390/make7010022","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7010022","pdf_url":"https://www.mdpi.com/2504-4990/7/1/22/pdf?version=1740392001","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/7/1/22/pdf?version=1740392001","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055184717","display_name":"Hanna Borgli","orcid":"https://orcid.org/0000-0001-9925-6134"},"institutions":[{"id":"https://openalex.org/I184942183","display_name":"University of Oslo","ror":"https://ror.org/01xtthb56","country_code":"NO","type":"education","lineage":["https://openalex.org/I184942183"]},{"id":"https://openalex.org/I2799829267","display_name":"Simula Research Laboratory","ror":"https://ror.org/00vn06n10","country_code":"NO","type":"facility","lineage":["https://openalex.org/I2799829267"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Hanna Borgli","raw_affiliation_strings":["Department of High-Performance Computing, Simula Research Laboratory, 0164 Oslo, Norway","Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, 0373 Oslo, Norway"],"raw_orcid":"https://orcid.org/0000-0001-9925-6134","affiliations":[{"raw_affiliation_string":"Department of High-Performance Computing, Simula Research Laboratory, 0164 Oslo, Norway","institution_ids":["https://openalex.org/I2799829267"]},{"raw_affiliation_string":"Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, 0373 Oslo, Norway","institution_ids":["https://openalex.org/I184942183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113578303","display_name":"H\u00e5kon Kvale Stensland","orcid":"https://orcid.org/0000-0002-1085-8540"},"institutions":[{"id":"https://openalex.org/I184942183","display_name":"University of Oslo","ror":"https://ror.org/01xtthb56","country_code":"NO","type":"education","lineage":["https://openalex.org/I184942183"]},{"id":"https://openalex.org/I2799829267","display_name":"Simula Research Laboratory","ror":"https://ror.org/00vn06n10","country_code":"NO","type":"facility","lineage":["https://openalex.org/I2799829267"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"H\u00e5kon Kvale Stensland","raw_affiliation_strings":["Department of High-Performance Computing, Simula Research Laboratory, 0164 Oslo, Norway","Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, 0373 Oslo, Norway"],"raw_orcid":"https://orcid.org/0000-0002-1085-8540","affiliations":[{"raw_affiliation_string":"Department of High-Performance Computing, Simula Research Laboratory, 0164 Oslo, Norway","institution_ids":["https://openalex.org/I2799829267"]},{"raw_affiliation_string":"Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, 0373 Oslo, Norway","institution_ids":["https://openalex.org/I184942183"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088962741","display_name":"P\u00e5l Halvorsen","orcid":"https://orcid.org/0000-0003-2073-7029"},"institutions":[{"id":"https://openalex.org/I4210153474","display_name":"Simula Metropolitan Center for Digital Engineering","ror":"https://ror.org/04xtarr15","country_code":"NO","type":"nonprofit","lineage":["https://openalex.org/I184531372","https://openalex.org/I2799829267","https://openalex.org/I4210153474"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"P\u00e5l Halvorsen","raw_affiliation_strings":["Department of Computer Science, Faculty of Technology, Art and Design, OsloMet, 0166 Oslo, Norway","Department of Holistic Systems, SimulaMet, 0170 Oslo, Norway"],"raw_orcid":"https://orcid.org/0000-0003-2073-7029","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Technology, Art and Design, OsloMet, 0166 Oslo, Norway","institution_ids":[]},{"raw_affiliation_string":"Department of Holistic Systems, SimulaMet, 0170 Oslo, Norway","institution_ids":["https://openalex.org/I4210153474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055184717"],"corresponding_institution_ids":["https://openalex.org/I184942183","https://openalex.org/I2799829267"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.9057,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.86130083,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"7","issue":"1","first_page":"22","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9980000257492065,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9959999918937683,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9947999715805054,"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/class","display_name":"Class (philosophy)","score":0.5713315010070801},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5489296913146973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4929180145263672},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4917345345020294},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3349730372428894}],"concepts":[{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5713315010070801},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5489296913146973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4929180145263672},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4917345345020294},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3349730372428894}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make7010022","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7010022","pdf_url":"https://www.mdpi.com/2504-4990/7/1/22/pdf?version=1740392001","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c457f5057fc34ad79512430879bf1b85","is_oa":true,"landing_page_url":"https://doaj.org/article/c457f5057fc34ad79512430879bf1b85","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 7, Iss 1, p 22 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make7010022","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7010022","pdf_url":"https://www.mdpi.com/2504-4990/7/1/22/pdf?version=1740392001","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4407874968.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W2108598243","https://openalex.org/W2131241448","https://openalex.org/W2776207810","https://openalex.org/W2981149872","https://openalex.org/W2997286550","https://openalex.org/W2999580839","https://openalex.org/W3035253074","https://openalex.org/W3082604781","https://openalex.org/W3092344722","https://openalex.org/W3132455321","https://openalex.org/W3162386519","https://openalex.org/W3213539234","https://openalex.org/W4224566678","https://openalex.org/W4327486354","https://openalex.org/W4362603432","https://openalex.org/W4379474533","https://openalex.org/W4385481295","https://openalex.org/W4388998820","https://openalex.org/W4389430914","https://openalex.org/W4390874575","https://openalex.org/W4391109864","https://openalex.org/W4392203599","https://openalex.org/W4393571644","https://openalex.org/W4402660140","https://openalex.org/W4402753685","https://openalex.org/W4402781391","https://openalex.org/W4402890475","https://openalex.org/W4402915908","https://openalex.org/W4404612908","https://openalex.org/W4405925280","https://openalex.org/W6678911119","https://openalex.org/W6772750526","https://openalex.org/W6803064041","https://openalex.org/W6852333398","https://openalex.org/W6853702739","https://openalex.org/W6859202844"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,77,92],"weakly":[3,88],"supervised":[4,89],"segmentation":[5,51,79,109,112],"approach":[6,83],"that":[7],"leverages":[8],"class":[9,29],"activation":[10,30],"maps":[11,31],"and":[12,87,104],"the":[13,39,46,59,67,71],"Segment":[14],"Anything":[15],"Model":[16],"to":[17,48],"generate":[18,49],"high-quality":[19],"masks":[20,65],"using":[21,70],"only":[22],"classification":[23],"data.":[24],"A":[25],"pre-trained":[26],"classifier":[27],"produces":[28],"that,":[32],"once":[33],"thresholded,":[34],"yield":[35],"bounding":[36],"boxes":[37,44],"encapsulating":[38],"regions":[40],"of":[41,97],"interest.":[42],"These":[43],"prompt":[45],"SAM":[47],"detailed":[50],"masks,":[52],"which":[53],"are":[54,114],"then":[55],"refined":[56],"by":[57],"selecting":[58],"best":[60],"overlap":[61],"with":[62],"automatically":[63],"generated":[64],"from":[66],"foundational":[68],"model":[69],"intersection":[72,94],"over":[73,95],"union":[74,96],"metric.":[75],"In":[76],"polyp":[78],"case":[80],"study,":[81],"our":[82],"outperforms":[84],"existing":[85],"zero-shot":[86],"methods,":[90],"achieving":[91],"mean":[93],"0.63.":[98],"This":[99],"method":[100],"offers":[101],"an":[102],"efficient":[103],"general":[105],"solution":[106],"for":[107],"image":[108],"tasks":[110],"where":[111],"data":[113],"scarce.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}