乐胖代购免代理版

{"id":"https://openalex.org/W2165748873","doi":"https://doi.org/10.1109/tai.1991.167102","title":"Boundary detection based on neural networks model","display_name":"Boundary detection based on neural networks model","publication_year":2002,"publication_date":"2002-12-10","ids":{"openalex":"https://openalex.org/W2165748873","doi":"https://doi.org/10.1109/tai.1991.167102","mag":"2165748873"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.1991.167102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5064492829","display_name":"D.C. Douglas Hung","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D.C.D. Hung","raw_affiliation_strings":["Department of Computer and Information Science, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029632449","display_name":"K.T. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K.T. Chen","raw_affiliation_strings":["Department of Computer and Information Science, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":57},"biblio":{"volume":null,"issue":null,"first_page":"254","last_page":"257"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.998,"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/T10320","display_name":"Neural Networks and Applications","score":0.998,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9861,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9857,"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/feedforward-neural-network","display_name":"Feedforward neural network","score":0.5122401}],"concepts":[{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.74387145},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.68959635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5603889},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.5482694},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.53813475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.53241277},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.5122401},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.46520218},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.45480108},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.417025},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3986801},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31799582},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.17845118},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.17776668}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.1991.167102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.77,"id":"https://metadata.un.org/sdg/11"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":15,"referenced_works":["https://openalex.org/W1554918148","https://openalex.org/W1622620102","https://openalex.org/W1968245656","https://openalex.org/W1991848143","https://openalex.org/W2084134149","https://openalex.org/W2087517326","https://openalex.org/W2101927907","https://openalex.org/W2128084896","https://openalex.org/W2468443503","https://openalex.org/W2490662969","https://openalex.org/W2503207332","https://openalex.org/W2740373864","https://openalex.org/W3017143921","https://openalex.org/W3148499377","https://openalex.org/W69476285"],"related_works":["https://openalex.org/W4385571583","https://openalex.org/W4378770497","https://openalex.org/W4308245303","https://openalex.org/W2910573937","https://openalex.org/W2385263368","https://openalex.org/W2079781215","https://openalex.org/W2049584446","https://openalex.org/W2014033564","https://openalex.org/W1978647244","https://openalex.org/W141820298"],"abstract_inverted_index":{"A":[0],"new":[1,67],"model":[2],"of":[3,13],"feedforward":[4],"neural":[5,31],"networks":[6],"is":[7,19,26,42],"proposed":[8],"for":[9,47],"solving":[10],"the":[11,35,78],"problem":[12],"robust":[14],"boundary":[15,49],"detection.":[16],"Structurally,":[17],"it":[18],"based":[20],"on":[21],"a":[22,29,39,52],"circular":[23],"mask":[24,79],"which":[25],"characterized":[27],"as":[28],"symmetrical":[30],"network.":[32],"By":[33],"analyzing":[34],"weighted":[36],"intermediate":[37],"pattern,":[38],"dominant":[40],"pattern":[41],"found":[43],"to":[44,72],"appear":[45],"repeatedly":[46],"similar":[48],"orientation.":[50],"Hence,":[51],"piecewise":[53],"linearized":[54],"edge":[55],"could":[56],"be":[57,70],"detected":[58],"by":[59,76],"this":[60,66],"approximation.":[61],"Experimental":[62],"results":[63],"show":[64],"that":[65],"architecture":[68],"can":[69],"applied":[71],"experience":[73],"scaling":[74],"effect":[75],"changing":[77],"size.<":[80],">":[83]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2165748873","counts_by_year":[],"updated_date":"2024-12-08T04:15:07.753773","created_date":"2016-06-24"}