{"id":"https://openalex.org/W2914478989","doi":"https://doi.org/10.1007/978-3-030-11018-5_35","title":"Small Defect Detection Using Convolutional Neural Network Features and Random Forests","display_name":"Small Defect Detection Using Convolutional Neural Network Features and Random Forests","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2914478989","doi":"https://doi.org/10.1007/978-3-030-11018-5_35","mag":"2914478989"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-11018-5_35","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-11018-5_35","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5026151886","display_name":"Xinghui Dong","orcid":"https://orcid.org/0000-0003-1047-427X"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xinghui Dong","raw_affiliation_strings":["Centre for Imaging Sciences, The University of Manchester, Manchester, M13 9PT, UK"],"affiliations":[{"raw_affiliation_string":"Centre for Imaging Sciences, The University of Manchester, Manchester, M13 9PT, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067224766","display_name":"Chris Taylor","orcid":"https://orcid.org/0000-0001-7867-9533"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chris J. Taylor","raw_affiliation_strings":["Centre for Imaging Sciences, The University of Manchester, Manchester, M13 9PT, UK"],"affiliations":[{"raw_affiliation_string":"Centre for Imaging Sciences, The University of Manchester, Manchester, M13 9PT, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058456050","display_name":"T.F. Cootes","orcid":"https://orcid.org/0000-0002-2695-9063"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tim F. Cootes","raw_affiliation_strings":["Centre for Imaging Sciences, The University of Manchester, Manchester, M13 9PT, UK"],"affiliations":[{"raw_affiliation_string":"Centre for Imaging Sciences, The University of Manchester, Manchester, M13 9PT, UK","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026151886"],"corresponding_institution_ids":["https://openalex.org/I28407311"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":25.3559,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.99717229,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"11132","issue":null,"first_page":"398","last_page":"412"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/softmax-function","display_name":"Softmax function","score":0.8850535154342651},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8040522933006287},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6629394292831421},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6588825583457947},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6327935457229614},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6101565361022949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6001322865486145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5995913743972778},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.53231281042099},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5012497901916504},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.4984767436981201},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.44017478823661804},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40980610251426697},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.1901337206363678}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8850535154342651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8040522933006287},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6629394292831421},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6588825583457947},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6327935457229614},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6101565361022949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6001322865486145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5995913743972778},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.53231281042099},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5012497901916504},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.4984767436981201},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.44017478823661804},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40980610251426697},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.1901337206363678},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/978-3-030-11018-5_35","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-11018-5_35","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/914439fc-d48f-4666-93bc-a3949f76294f","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/914439fc-d48f-4666-93bc-a3949f76294f","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Dong, X, Taylor, C & Cootes, T F 2019, Small Defect Detection Using Convolutional Neural Network Features and Random Forests. in European Conference on Computer Vision. vol. 11132, Lecture Notes in Computer Science, vol. 11132, Springer Nature, Switzerland, pp. 398-412. https://doi.org/10.1007/978-3-030-11018-5_35","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"mag:3091068379","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201902211332298554","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Lecture notes in computer science","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.5299999713897705,"display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G7571721515","display_name":null,"funder_award_id":"EP/L022125/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1562291184","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1948751323","https://openalex.org/W2002444680","https://openalex.org/W2009621568","https://openalex.org/W2014774208","https://openalex.org/W2019117580","https://openalex.org/W2062118960","https://openalex.org/W2094334775","https://openalex.org/W2095338679","https://openalex.org/W2102605133","https://openalex.org/W2132763323","https://openalex.org/W2147237076","https://openalex.org/W2151103935","https://openalex.org/W2164598857","https://openalex.org/W2167510172","https://openalex.org/W2549196305","https://openalex.org/W2589306531","https://openalex.org/W2746808752","https://openalex.org/W2750925197","https://openalex.org/W2765854388","https://openalex.org/W2766338559","https://openalex.org/W2902323275","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2962860144","https://openalex.org/W2963417518","https://openalex.org/W2963459241","https://openalex.org/W2964121744"],"related_works":["https://openalex.org/W3034884618","https://openalex.org/W4225852842","https://openalex.org/W2742991909","https://openalex.org/W4306753247","https://openalex.org/W2964383635","https://openalex.org/W3163524149","https://openalex.org/W4319301798","https://openalex.org/W2912288872","https://openalex.org/W2767651786","https://openalex.org/W2563096758"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}