{"id":"https://openalex.org/W4200377363","doi":"https://doi.org/10.1145/3490035.3490281","title":"SCNet","display_name":"SCNet","publication_year":2021,"publication_date":"2021-12-14","ids":{"openalex":"https://openalex.org/W4200377363","doi":"https://doi.org/10.1145/3490035.3490281"},"language":"en","primary_location":{"id":"doi:10.1145/3490035.3490281","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490035.3490281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth Indian Conference on Computer Vision, Graphics and Image Processing","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/A5080593042","display_name":"Hrishikesh Sharma","orcid":"https://orcid.org/0000-0001-8550-7668"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hrishikesh Sharma","raw_affiliation_strings":["TCS Research, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078282761","display_name":"Prakhar Pradhan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prakhar Pradhan","raw_affiliation_strings":["TCS Research, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, Bengaluru, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015757476","display_name":"P. Balamuralidhar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Balamuralidhar P.","raw_affiliation_strings":["TCS Research, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, Bengaluru, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080593042"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.539,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.65136983,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9901999831199646,"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/T11850","display_name":"Concrete Corrosion and Durability","score":0.9686999917030334,"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/segmentation","display_name":"Segmentation","score":0.8473506569862366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7184107303619385},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7177723050117493},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6644105911254883},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5992300510406494},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5948110222816467},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5794259309768677},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5674233436584473},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5019505023956299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49531975388526917},{"id":"https://openalex.org/keywords/zigzag","display_name":"Zigzag","score":0.43967896699905396},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41891559958457947},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37951716780662537},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.352944552898407},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34211549162864685},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25341618061065674},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1503111720085144},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1102452278137207},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07308503985404968}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8473506569862366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7184107303619385},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7177723050117493},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6644105911254883},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5992300510406494},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5948110222816467},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5794259309768677},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5674233436584473},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5019505023956299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49531975388526917},{"id":"https://openalex.org/C192271897","wikidata":"https://www.wikidata.org/wiki/Q198438","display_name":"Zigzag","level":2,"score":0.43967896699905396},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41891559958457947},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37951716780662537},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.352944552898407},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34211549162864685},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25341618061065674},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1503111720085144},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1102452278137207},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07308503985404968},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3490035.3490281","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490035.3490281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W845365781","https://openalex.org/W1966716734","https://openalex.org/W1971014294","https://openalex.org/W2137160061","https://openalex.org/W2406523001","https://openalex.org/W2407692387","https://openalex.org/W2780861787","https://openalex.org/W2799581210","https://openalex.org/W2804860796","https://openalex.org/W2884585870","https://openalex.org/W2899242765","https://openalex.org/W2912350898","https://openalex.org/W2919816425","https://openalex.org/W2922073063","https://openalex.org/W2962891704","https://openalex.org/W2963321359","https://openalex.org/W2964118266","https://openalex.org/W3012540514","https://openalex.org/W3016245448"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,46],"and":[2,13,43,86,121,135,140],"localization":[3],"is":[4,35,51,56,67,181],"an":[5,36,52,111],"important":[6,53],"vision":[7],"problem,":[8,117],"having":[9],"multiple":[10],"applications.":[11],"Effective":[12],"generic":[14],"semantic":[15],"segmentation":[16,116,126],"of":[17,61,114,119,125,130,154,159],"anomalous":[18,26],"regions":[19,27],"on":[20,188],"various":[21],"different":[22,160],"surfaces,":[23],"where":[24],"most":[25],"inherently":[28],"do":[29],"not":[30],"have":[31],"any":[32,177],"obvious":[33],"pattern,":[34],"active":[37],"research":[38],"problem.":[39],"Periodic":[40],"health":[41],"monitoring":[42],"fault":[44],"(anomaly)":[45],"in":[47,74,143],"vast":[48],"infrastructures,":[49,161],"which":[50],"safety-related":[54],"task,":[55],"one":[57],"such":[58],"application":[59],"area":[60],"anomaly":[62],"segmentation.":[63],"However,":[64],"this":[65,107],"task":[66],"quite":[68],"challenging":[69],"due":[70],"to":[71,104,157,183],"large":[72],"variations":[73],"surface":[75,88],"faults,":[76],"texture-less":[77],"construction":[78],"material/background,":[79],"lighting":[80],"conditions":[81],"etc.":[82],"Cracks":[83],"are":[84,99],"critical":[85],"frequent":[87],"faults":[89,103],"that":[90,118],"manifest":[91],"as":[92,194],"extreme":[93],"zigzag-shaped":[94],"thin,":[95],"elongated":[96],"regions.":[97],"They":[98],"among":[100],"the":[101,123,137,169],"hardest":[102],"detect.":[105],"In":[106],"work,":[108],"we":[109],"address":[110],"open":[112],"aspect":[113],"crack":[115],"generalizing":[120],"improving":[122],"performance":[124,187],"across":[127],"a":[128,144,152,173],"variety":[129,153],"scenarios.":[131],"We":[132],"carefully":[133],"study":[134],"abstract":[136],"sub-problems":[138],"involved":[139],"solve":[141],"them":[142],"broader":[145],"context,":[146],"making":[147],"our":[148,165],"solution":[149],"generic.":[150],"On":[151],"datasets":[155],"related":[156],"surveillance":[158],"under":[162],"varying":[163],"conditions,":[164],"model":[166,180],"consistently":[167],"outperforms":[168],"state-of-the-art":[170],"algorithms":[171],"by":[172],"significant":[174],"margin,":[175],"without":[176],"bells-and-whistles.":[178],"The":[179],"expected":[182],"show":[184],"similar":[185],"improved":[186],"(indoor)":[189],"material":[190],"quality":[191],"inspection":[192],"tasks":[193],"well.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2021-12-31T00:00:00"}
