{"id":"https://openalex.org/W4385413676","doi":"https://doi.org/10.1109/tai.2023.3299903","title":"Modified ResNet-152 Network With Hybrid Pyramidal Pooling for Local Change Detection","display_name":"Modified ResNet-152 Network With Hybrid Pyramidal Pooling for Local Change Detection","publication_year":2023,"publication_date":"2023-07-31","ids":{"openalex":"https://openalex.org/W4385413676","doi":"https://doi.org/10.1109/tai.2023.3299903"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2023.3299903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2023.3299903","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on 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/A5101824900","display_name":"Manoj Kumar Panda","orcid":"https://orcid.org/0009-0002-5021-2741"},"institutions":[{"id":"https://openalex.org/I4210139271","display_name":"GIET University","ror":"https://ror.org/051f2wp73","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210139271"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Manoj Kumar Panda","raw_affiliation_strings":["GIET University, Gunupur, India"],"affiliations":[{"raw_affiliation_string":"GIET University, Gunupur, India","institution_ids":["https://openalex.org/I4210139271"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026675739","display_name":"Badri Narayan Subudhi","orcid":"https://orcid.org/0000-0002-4378-0065"},"institutions":[{"id":"https://openalex.org/I4210127441","display_name":"Indian Institute of Technology Jammu","ror":"https://ror.org/02f0vsw63","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210127441"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Badri Narayan Subudhi","raw_affiliation_strings":["Indian Institute of Technology Jammu, Jammu, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Jammu, Jammu, India","institution_ids":["https://openalex.org/I4210127441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005180011","display_name":"T. Veerakumar","orcid":"https://orcid.org/0000-0001-9084-1847"},"institutions":[{"id":"https://openalex.org/I4210109276","display_name":"National Institute of Technology Goa","ror":"https://ror.org/01vmfpj79","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210109276"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Thangaraj Veerakumar","raw_affiliation_strings":["National Institute of Technology Goa, Ponda, India"],"affiliations":[{"raw_affiliation_string":"National Institute of Technology Goa, Ponda, India","institution_ids":["https://openalex.org/I4210109276"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019388627","display_name":"Vinit Jakhetiya","orcid":"https://orcid.org/0000-0002-8325-4908"},"institutions":[{"id":"https://openalex.org/I4210127441","display_name":"Indian Institute of Technology Jammu","ror":"https://ror.org/02f0vsw63","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210127441"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vinit Jakhetiya","raw_affiliation_strings":["Indian Institute of Technology Jammu, Jammu, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Jammu, Jammu, India","institution_ids":["https://openalex.org/I4210127441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101824900"],"corresponding_institution_ids":["https://openalex.org/I4210139271"],"apc_list":null,"apc_paid":null,"fwci":5.6786,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.96513427,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"5","issue":"4","first_page":"1599","last_page":"1612"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9897000193595886,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9886999726295471,"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/pooling","display_name":"Pooling","score":0.7867457270622253},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7517935633659363},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6996216773986816},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6319261789321899},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5764861106872559},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5441786050796509},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5091874003410339},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4958373010158539},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43993017077445984},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.43285924196243286},{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.4271523952484131},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4139876961708069},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37972044944763184},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1447015404701233}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7867457270622253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7517935633659363},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6996216773986816},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6319261789321899},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5764861106872559},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5441786050796509},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5091874003410339},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4958373010158539},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43993017077445984},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.43285924196243286},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.4271523952484131},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4139876961708069},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37972044944763184},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1447015404701233},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2023.3299903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2023.3299903","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G134569333","display_name":null,"funder_award_id":"TIH/iHub Drishti/Project/2022-23/35","funder_id":"https://openalex.org/F4320319038","funder_display_name":"Indian Institute of Technology Jodhpur"}],"funders":[{"id":"https://openalex.org/F4320319038","display_name":"Indian Institute of Technology Jodhpur","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1486354537","https://openalex.org/W1525699417","https://openalex.org/W1584759658","https://openalex.org/W1964127768","https://openalex.org/W1969977005","https://openalex.org/W1982853888","https://openalex.org/W1988061476","https://openalex.org/W1994634851","https://openalex.org/W2041868356","https://openalex.org/W2052524720","https://openalex.org/W2065914597","https://openalex.org/W2104433781","https://openalex.org/W2111918405","https://openalex.org/W2116076678","https://openalex.org/W2118143383","https://openalex.org/W2127070222","https://openalex.org/W2131479503","https://openalex.org/W2132461991","https://openalex.org/W2141572457","https://openalex.org/W2148290050","https://openalex.org/W2158604775","https://openalex.org/W2194775991","https://openalex.org/W2394875178","https://openalex.org/W2412782625","https://openalex.org/W2414168010","https://openalex.org/W2417256080","https://openalex.org/W2512785428","https://openalex.org/W2525668722","https://openalex.org/W2560023338","https://openalex.org/W2605856284","https://openalex.org/W2606629906","https://openalex.org/W2624386319","https://openalex.org/W2751961297","https://openalex.org/W2759692151","https://openalex.org/W2768086131","https://openalex.org/W2771659028","https://openalex.org/W2783946051","https://openalex.org/W2789576005","https://openalex.org/W2886956694","https://openalex.org/W2888845200","https://openalex.org/W2901951655","https://openalex.org/W2909051837","https://openalex.org/W2940797985","https://openalex.org/W2947033361","https://openalex.org/W2953452037","https://openalex.org/W2963762195","https://openalex.org/W2963846024","https://openalex.org/W2970649833","https://openalex.org/W2990524584","https://openalex.org/W3024617482","https://openalex.org/W3105220622","https://openalex.org/W3136426854","https://openalex.org/W3192920216","https://openalex.org/W4205241707","https://openalex.org/W4283796179","https://openalex.org/W4310269137"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W3103989898","https://openalex.org/W4287804464","https://openalex.org/W3211292372","https://openalex.org/W803346624"],"abstract_inverted_index":{"In":[0],"this":[1],"article,":[2],"we":[3],"put":[4],"forth":[5],"a":[6,29,34,46,67,96,168,177,181],"unique":[7],"attempt":[8],"to":[9,118,137,173,189,246],"detect":[10],"the":[11,20,51,58,61,76,109,113,127,139,143,146,186,191,196,203,219,230,233],"local":[12],"changes":[13],"in":[14,126,133,145],"challenging":[15,154],"video":[16,148,241],"scenes":[17],"by":[18,208,218],"exploring":[19],"capabilities":[21],"of":[22,45,60,98,124,161,202,232],"an":[23,90,239],"encoder-decoder":[24],"type":[25],"network":[26,43,49,115,159],"that":[27,150,166],"employs":[28],"modified":[30,47],"ResNet-152":[31,48],"architecture":[32,101],"with":[33,238],"multi-scale":[35,120],"feature":[36,171],"extraction":[37],"(MFE)":[38],"framework.":[39],"The":[40,71,122,156,200,215],"proposed":[41,89,157,204,220,234],"encoder":[42,73,114],"consists":[44,160],"where":[50,108],"initial":[52],"two":[53],"blocks":[54,63],"are":[55,64,116,222],"freeze":[56],"and":[57,79,103,198,243],"weights":[59],"last":[62],"learned":[65],"using":[66],"transfer":[68],"learning":[69],"mechanism.":[70],"said":[72],"can":[74,151],"reduce":[75],"computational":[77],"complexity":[78],"extract":[80,119],"fine":[81],"as":[82,84,195,225,227],"well":[83,226],"coarse-scale":[85],"features.":[86,121],"We":[87],"have":[88],"MFE":[91,128],"mechanism":[92],"block":[93,129],"which":[94],"is":[95,183,206,236,244],"hybridization":[97],"pyramidal":[99],"pooling":[100,135],"(PPA),":[102],"various":[104,153],"atrous":[105],"convolutional":[106],"layers":[107,165],"high-level":[110],"features":[111],"from":[112,170],"utilized":[117],"use":[123],"PPA":[125],"preserves":[130],"maximum":[131],"value":[132],"every":[134],"area,":[136],"retain":[138],"contextual":[140],"relationship":[141],"between":[142],"pixels":[144],"complex":[147],"frames":[149],"handle":[152],"scenes.":[155],"decoder":[158],"stacked":[162],"transposed":[163],"convolution":[164],"learn":[167],"mapping":[169],"space":[172],"image":[174],"space,":[175],"predicting":[176],"score":[178,187],"map.":[179],"Then,":[180],"threshold":[182],"applied":[184],"on":[185],"map":[188],"get":[190],"binary":[192],"class":[193],"labels":[194],"background":[197],"foreground.":[199],"performance":[201],"scheme":[205],"validated":[207],"testing":[209],"it":[210],"against":[211],"31":[212],"state-of-the-art":[213],"techniques.":[214],"results":[216],"obtained":[217],"method":[221],"corroborated":[223],"qualitatively":[224],"quantitatively.":[228],"Further,":[229],"efficacy":[231],"algorithm":[235],"verified":[237],"unseen":[240],"setup":[242],"found":[245],"provide":[247],"better":[248],"performance.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":14},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
