{"id":"https://openalex.org/W2130391384","doi":"https://doi.org/10.1142/s0218001401001428","title":"HIERARCHICAL SHAPE DESCRIPTION AND SIMILARITY-INVARIANT RECOGNITION USING GRADIENT PROPAGATION","display_name":"HIERARCHICAL SHAPE DESCRIPTION AND SIMILARITY-INVARIANT RECOGNITION USING GRADIENT PROPAGATION","publication_year":2001,"publication_date":"2001-12-01","ids":{"openalex":"https://openalex.org/W2130391384","doi":"https://doi.org/10.1142/s0218001401001428","mag":"2130391384"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001401001428","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001401001428","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5028863480","display_name":"J. Ben-Arie","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"JEZEKIEL BEN-ARIE","raw_affiliation_strings":["EECS Department, University of Illinois at Chicago, Chicago, IL 60607, USA","Department of Electrical and Computer Engineering,University of Illinois at Chicago"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of Illinois at Chicago, Chicago, IL 60607, USA","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering,University of Illinois at Chicago","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100644463","display_name":"Zhiqian Wang","orcid":"https://orcid.org/0000-0002-4023-3664"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"ZHIQIAN WANG","raw_affiliation_strings":["EECS Department, University of Illinois at Chicago, Chicago, IL 60607, USA"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of Illinois at Chicago, Chicago, IL 60607, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5028863480"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.19482052,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":"08","first_page":"1251","last_page":"1261"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9983999729156494,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9919999837875366,"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/gradient-descent","display_name":"Gradient descent","score":0.5552473068237305},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5412644147872925},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.535631000995636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5055370330810547},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.5044339895248413},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4960995614528656},{"id":"https://openalex.org/keywords/active-shape-model","display_name":"Active shape model","score":0.4938879609107971},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4927974045276642},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43536436557769775},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.42728447914123535},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4265413284301758},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41153115034103394},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36884695291519165},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25681090354919434},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.12419712543487549},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11747214198112488}],"concepts":[{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5552473068237305},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5412644147872925},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.535631000995636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5055370330810547},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.5044339895248413},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4960995614528656},{"id":"https://openalex.org/C129641003","wikidata":"https://www.wikidata.org/wiki/Q267189","display_name":"Active shape model","level":3,"score":0.4938879609107971},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4927974045276642},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43536436557769775},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.42728447914123535},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4265413284301758},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41153115034103394},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36884695291519165},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25681090354919434},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.12419712543487549},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11747214198112488},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s0218001401001428","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001401001428","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.88.1913","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.88.1913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.ece.uic.edu/papers/2001/apropag.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W96629785","https://openalex.org/W1991113069","https://openalex.org/W2011874170","https://openalex.org/W2077246452","https://openalex.org/W2104095591","https://openalex.org/W2114399594","https://openalex.org/W2123669034","https://openalex.org/W2154186675","https://openalex.org/W2160685330","https://openalex.org/W2162837059","https://openalex.org/W2565152771"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W2115214301","https://openalex.org/W2070318884","https://openalex.org/W1496493270","https://openalex.org/W1981531423","https://openalex.org/W1679012645","https://openalex.org/W2011939812"],"abstract_inverted_index":{"This":[0,16],"paper":[1],"presents":[2],"a":[3,22,80,97,114,172],"novel":[4,50],"hierarchical":[5,159],"shape":[6,37,122,129],"description":[7,82,118,130,160],"scheme":[8,143,175],"based":[9,176],"on":[10,177],"propagating":[11],"the":[12,64,103,120,128,146,156,178],"image":[13],"gradient":[14,30,65,104],"radially.":[15],"radial":[17],"propagation":[18],"is":[19,57,100,112,131,144,161],"equivalent":[20],"to":[21,59,133],"vectorial":[23,51],"convolution":[24],"with":[25,171],"sector":[26],"elements.":[27],"The":[28,158],"propagated":[29],"field":[31,105],"collides":[32,107],"at":[33,108],"centers":[34],"of":[35,45,63,70,83,119,141,155,168],"convex/concave":[36],"components,":[38],"which":[39,111],"can":[40],"be":[41],"detected":[42],"as":[43],"points":[44],"high":[46],"directional":[47],"disparity.":[48],"A":[49],"disparity":[52],"measure":[53,60,72],"called":[54],"Cancellation":[55],"Energy":[56],"used":[58,164],"this":[61,71,142],"collision":[62],"field,":[66],"and":[67,85,88,93,116,136],"local":[68],"maxima":[69],"yield":[73],"feature":[74,77,147],"tokens.":[75],"These":[76],"tokens":[78,148],"form":[79],"compact":[81],"shapes":[84,170],"their":[86,90],"components":[87],"indicate":[89],"central":[91],"locations":[92],"sizes.":[94],"In":[95],"addition,":[96],"Gradient":[98,179],"Signature":[99],"formed":[101],"by":[102],"that":[106,127,145],"each":[109],"center,":[110],"itself":[113],"robust":[115,132],"size-independent":[117],"corresponding":[121],"component.":[123],"Experimental":[124],"results":[125],"demonstrate":[126],"distortion,":[134],"noise":[135],"clutter.":[137],"An":[138],"important":[139],"advantage":[140],"are":[149],"obtained":[150],"pre-attentively,":[151],"without":[152],"prior":[153],"understanding":[154],"image.":[157],"also":[162],"successfully":[163],"for":[165],"similarity-invariant":[166],"recognition":[167],"2D":[169],"multi-dimensional":[173],"indexing":[174],"Signature.":[180]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
