{"id":"https://openalex.org/W2398733480","doi":"https://doi.org/10.1109/icassp.2016.7472024","title":"Exploiting sparsity for image-based object surface anomaly detection","display_name":"Exploiting sparsity for image-based object surface anomaly detection","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2398733480","doi":"https://doi.org/10.1109/icassp.2016.7472024","mag":"2398733480"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5111408624","display_name":"Woon Huei Chai","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Woon Huei Chai","raw_affiliation_strings":["Rolls-Royce @ Nanyang Technological University Corporate Lab, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rolls-Royce @ Nanyang Technological University Corporate Lab, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049730546","display_name":"Shen-Shyang Ho","orcid":"https://orcid.org/0000-0002-0353-7159"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shen-Shyang Ho","raw_affiliation_strings":["School of Computer Engineering, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021045741","display_name":"Chi-Keong Goh","orcid":"https://orcid.org/0000-0002-4250-7307"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chi-Keong Goh","raw_affiliation_strings":["Rolls-Royce Singapore Pte Ltd, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rolls-Royce Singapore Pte Ltd, Singapore","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4416,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78363959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"2011","issue":null,"first_page":"1986","last_page":"1990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994999766349792,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994999766349792,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/anomaly-detection","display_name":"Anomaly detection","score":0.7846136093139648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.722953736782074},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7009502053260803},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5930413603782654},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.573276698589325},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5721098184585571},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5459796190261841},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5366854667663574},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5363878607749939},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5080506801605225},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4790250360965729},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47198253870010376},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.45701223611831665},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.4289630353450775},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42746907472610474},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.22296389937400818},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13385522365570068},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08166232705116272}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7846136093139648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.722953736782074},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7009502053260803},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5930413603782654},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.573276698589325},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5721098184585571},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5459796190261841},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5366854667663574},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5363878607749939},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5080506801605225},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4790250360965729},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47198253870010376},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.45701223611831665},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.4289630353450775},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42746907472610474},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.22296389937400818},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13385522365570068},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08166232705116272},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"},{"id":"https://openalex.org/F4320320766","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302"},{"id":"https://openalex.org/F4320335158","display_name":"Energy Research Institute, Nanyang Technological University","ror":"https://ror.org/02e7b5302"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W42722137","https://openalex.org/W1602011302","https://openalex.org/W1965696824","https://openalex.org/W1980501414","https://openalex.org/W1980912826","https://openalex.org/W1986703546","https://openalex.org/W2004313226","https://openalex.org/W2012931101","https://openalex.org/W2021345820","https://openalex.org/W2044239833","https://openalex.org/W2076666921","https://openalex.org/W2095581126","https://openalex.org/W2101807845","https://openalex.org/W2105464873","https://openalex.org/W2105497548","https://openalex.org/W2112680570","https://openalex.org/W2122361470","https://openalex.org/W2122646361","https://openalex.org/W2129812935","https://openalex.org/W2153663612","https://openalex.org/W6609998551"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037","https://openalex.org/W4377864969","https://openalex.org/W3030345572"],"abstract_inverted_index":{"The":[0,92],"anomaly":[1,22],"detection":[2,23,47,129],"task":[3,130],"plays":[4],"an":[5,54,61,84,114,125],"important":[6],"role":[7],"in":[8,11,18,40,45,60],"quality":[9],"control":[10],"many":[12,19],"industrial":[13,126],"or":[14],"manufacturing":[15],"processes.":[16],"However,":[17],"such":[20],"processes,":[21],"is":[24],"done":[25],"visually":[26],"by":[27],"human":[28],"experts":[29],"who":[30],"have":[31],"in-depth":[32],"knowledge":[33],"and":[34,77,107],"vast":[35],"experience":[36],"on":[37,64,88,119],"a":[38,120],"product":[39],"order":[41],"to":[42,82,133],"perform":[43],"well":[44],"the":[46,65,80,135],"task.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52],"present":[53],"approach":[55,100],"that":[56],"(i)":[57,103],"identifies":[58],"anomalies":[59,104,109],"image":[62,72,85,115,122],"based":[63,87],"sparse":[66,75,97],"residuals":[67],"(or":[68],"errors)":[69],"obtained":[70],"during":[71],"reconstruction":[73],"using":[74],"representation":[76],"(ii)":[78,108],"learns":[79],"threshold":[81],"classify":[83],"pixel":[86],"its":[89],"residual":[90],"value.":[91],"intuitions":[93],"for":[94,124],"our":[95,138],"proposed":[96,139],"approximation":[98],"driven":[99],"are,":[101],"namely:":[102],"are":[105,110,131],"infrequent":[106],"unwanted":[111],"portions":[112],"of":[113,137],"reconstruction.":[116],"Empirical":[117],"results":[118],"real-world":[121],"dataset":[123],"surface":[127],"defect":[128],"used":[132],"demonstrate":[134],"feasibility":[136],"approach.":[140]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}