{"id":"https://openalex.org/W7225114530","doi":"https://doi.org/10.52088/ijesty.v6i4.1989","title":"Revisiting Attention Modules for Still-Image Human Action Recognition: A Multi-Seed Evaluation on Stanford-40","display_name":"Revisiting Attention Modules for Still-Image Human Action Recognition: A Multi-Seed Evaluation on Stanford-40","publication_year":2026,"publication_date":"2026-11-02","ids":{"openalex":"https://openalex.org/W7225114530","doi":"https://doi.org/10.52088/ijesty.v6i4.1989"},"language":"en","primary_location":{"id":"doi:10.52088/ijesty.v6i4.1989","doi":"https://doi.org/10.52088/ijesty.v6i4.1989","is_oa":true,"landing_page_url":"https://doi.org/10.52088/ijesty.v6i4.1989","pdf_url":"https://ijesty.org/index.php/ijesty/article/download/1989/829","source":{"id":"https://openalex.org/S4210197357","display_name":"International Journal of Engineering Science and Information Technology","issn_l":"2775-2674","issn":["2775-2674"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Engineering, Science and Information Technology","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ijesty.org/index.php/ijesty/article/download/1989/829","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081051011","display_name":"Rokhmat Febrianto","orcid":"https://orcid.org/0009-0004-9814-122X","observed_orcids":["https://orcid.org/0009-0004-9814-122X"]},"institutions":[{"id":"https://openalex.org/I4400573250","display_name":"Universitas Prasetiya Mulya","ror":"https://ror.org/01wsc1g26","country_code":"ID","type":"education","lineage":["https://openalex.org/I4400573250"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Rokhmat Febrianto","raw_affiliation_strings":["Universitas Prasetiya Mulya"],"raw_orcid":"https://orcid.org/0009-0004-9814-122X","affiliations":[{"raw_affiliation_string":"Universitas Prasetiya Mulya","institution_ids":["https://openalex.org/I4400573250"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160382373","display_name":"Ayomi Sasmito","orcid":"https://orcid.org/0000-0001-9798-2458","observed_orcids":["https://orcid.org/0000-0001-9798-2458"]},"institutions":[{"id":"https://openalex.org/I4400573250","display_name":"Universitas Prasetiya Mulya","ror":"https://ror.org/01wsc1g26","country_code":"ID","type":"education","lineage":["https://openalex.org/I4400573250"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Ayomi Sasmito","raw_affiliation_strings":["Universitas Prasetiya Mulya"],"raw_orcid":"https://orcid.org/0000-0001-9798-2458","affiliations":[{"raw_affiliation_string":"Universitas Prasetiya Mulya","institution_ids":["https://openalex.org/I4400573250"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4400573250"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80215642,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"4","first_page":"200","last_page":"211"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9765999913215637,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9765999913215637,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.016499999910593033,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.002099999925121665,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/attention-modules","display_name":"attention modules","score":0.9860000014305115},{"id":"https://openalex.org/keywords/human-action-recognition","display_name":"human action recognition","score":0.8360000252723694},{"id":"https://openalex.org/keywords/still-images","display_name":"still images","score":0.7110000252723694},{"id":"https://openalex.org/keywords/squeeze-and-excitation","display_name":"squeeze-and-excitation","score":0.9440000057220459},{"id":"https://openalex.org/keywords/convolutional-block-attention-module","display_name":"CBAM","score":0.7950000166893005},{"id":"https://openalex.org/keywords/efficient-channel-attention","display_name":"efficient channel attention","score":0.9869999885559082},{"id":"https://openalex.org/keywords/simam","display_name":"SimAM","score":0.9919999837875366},{"id":"https://openalex.org/keywords/resnet34","display_name":"ResNet34","score":0.8080000281333923},{"id":"https://openalex.org/keywords/train-test-split","display_name":"train-test split","score":0.6859999895095825},{"id":"https://openalex.org/keywords/random-seed","display_name":"random seed","score":0.6539999842643738},{"id":"https://openalex.org/keywords/evaluation-protocol","display_name":"evaluation protocol","score":0.5260000228881836},{"id":"https://openalex.org/keywords/reporting-checklist","display_name":"reporting checklist","score":0.6039999723434448},{"id":"https://openalex.org/keywords/inference-latency","display_name":"inference latency","score":0.6690000295639038}],"concepts":[{"id":"https://openalex.org/C186282968","wikidata":"https://www.wikidata.org/wiki/Q1434261","display_name":"McNemar's test","level":2,"score":0.9150999784469604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5228000283241272},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5203999876976013},{"id":"https://openalex.org/C206041023","wikidata":"https://www.wikidata.org/wiki/Q1751970","display_name":"Wilcoxon signed-rank test","level":3,"score":0.510699987411499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4828000068664551},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4325999915599823},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C2779356329","wikidata":"https://www.wikidata.org/wiki/Q922625","display_name":"Checklist","level":2,"score":0.391400009393692},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3878999948501587},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.38100001215934753},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.3783999979496002},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3463999927043915},{"id":"https://openalex.org/C98347192","wikidata":"https://www.wikidata.org/wiki/Q7705804","display_name":"Test score","level":3,"score":0.33570000529289246},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2987000048160553},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2888999879360199},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C102959455","wikidata":"https://www.wikidata.org/wiki/Q7313954","display_name":"Repeated measures design","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C99476002","wikidata":"https://www.wikidata.org/wiki/Q42297","display_name":"Analysis of variance","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.52088/ijesty.v6i4.1989","doi":"https://doi.org/10.52088/ijesty.v6i4.1989","is_oa":true,"landing_page_url":"https://doi.org/10.52088/ijesty.v6i4.1989","pdf_url":"https://ijesty.org/index.php/ijesty/article/download/1989/829","source":{"id":"https://openalex.org/S4210197357","display_name":"International Journal of Engineering Science and Information Technology","issn_l":"2775-2674","issn":["2775-2674"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Engineering, Science and Information Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.52088/ijesty.v6i4.1989","doi":"https://doi.org/10.52088/ijesty.v6i4.1989","is_oa":true,"landing_page_url":"https://doi.org/10.52088/ijesty.v6i4.1989","pdf_url":"https://ijesty.org/index.php/ijesty/article/download/1989/829","source":{"id":"https://openalex.org/S4210197357","display_name":"International Journal of Engineering Science and Information Technology","issn_l":"2775-2674","issn":["2775-2674"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Engineering, Science and Information Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320328101","display_name":"Universitas Prasetiya Mulya","ror":"https://ror.org/01wsc1g26"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225114530.pdf","grobid_xml":"https://content.openalex.org/works/W7225114530.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W2038765747","https://openalex.org/W2884585870","https://openalex.org/W2963420686","https://openalex.org/W3034552520","https://openalex.org/W3086100325","https://openalex.org/W3117876421","https://openalex.org/W3133605945","https://openalex.org/W3183977027","https://openalex.org/W3190543630","https://openalex.org/W3212386989","https://openalex.org/W3212604410","https://openalex.org/W4221151810","https://openalex.org/W4223430324","https://openalex.org/W4223538986","https://openalex.org/W4226239016","https://openalex.org/W4283819769","https://openalex.org/W4295308620","https://openalex.org/W4313886702","https://openalex.org/W4320039061","https://openalex.org/W4380785753","https://openalex.org/W4385576721","https://openalex.org/W4387022349","https://openalex.org/W4388895451","https://openalex.org/W4392232009","https://openalex.org/W4392741075","https://openalex.org/W4396541948","https://openalex.org/W4401256393","https://openalex.org/W4401805305","https://openalex.org/W4401951602","https://openalex.org/W4402827736","https://openalex.org/W4409415146","https://openalex.org/W4416767131","https://openalex.org/W4417251384","https://openalex.org/W7125433159","https://openalex.org/W7128301462","https://openalex.org/W7160135851","https://openalex.org/W7172379234"],"related_works":["https://openalex.org/W7154301277","https://openalex.org/W7212901538","https://openalex.org/W4320039061","https://openalex.org/W4226526933","https://openalex.org/W2964233791","https://openalex.org/W4410780137","https://openalex.org/W3003749315","https://openalex.org/W3166838308","https://openalex.org/W4285243277","https://openalex.org/W3011008797"],"abstract_inverted_index":{"Attention":[0,65,70],"modules":[1,228,241],"such":[2,240],"as":[3],"Squeeze-and-Excitation":[4,60],"are":[5,38],"often":[6],"reported":[7,50,223],"to":[8,140,202],"improve":[9],"convolutional":[10],"neural":[11],"networks":[12],"for":[13,236],"human":[14],"action":[15],"recognition":[16],"in":[17,209],"still":[18],"images.":[19],"Most":[20],"of":[21,167,239],"these":[22],"reports,":[23],"however,":[24],"rely":[25],"on":[26,34,85,185],"a":[27,54,116,131,147,189,231],"single":[28],"training":[29,97],"run,":[30],"and":[31,72,83,113,121,173,179,219,230],"published":[32],"scores":[33,224],"the":[35,49,62,73,86,127,164,168,186,216,227],"same":[36],"benchmark":[37],"frequently":[39],"obtained":[40],"under":[41,53,90],"different":[42],"train\u2013test":[43],"splits.":[44],"This":[45],"study":[46],"examines":[47],"whether":[48],"benefit":[51],"remains":[52],"controlled":[55],"evaluation.":[56],"Four":[57],"modules,":[58],"namely":[59],"(SE),":[61],"Convolutional":[63],"Block":[64],"Module":[66],"(CBAM),":[67],"Efficient":[68],"Channel":[69],"(ECA),":[71],"parameter-free":[74],"SimAM,":[75],"were":[76,107],"inserted":[77],"into":[78],"ResNet-34":[79],"at":[80],"four":[81,104,145],"positions":[82],"trained":[84,101],"Stanford-40":[87],"Actions":[88],"dataset":[89],"its":[91],"official":[92,128],"split":[93,129,134],"with":[94,109,130],"one":[95],"fixed":[96],"recipe,":[98],"giving":[99],"44":[100],"models.":[102],"The":[103,212],"all-stage":[105],"configurations":[106],"repeated":[108],"six":[110,155],"random":[111,132],"seeds":[112],"compared":[114],"using":[115],"paired":[117],"Wilcoxon":[118],"signed-rank":[119],"test":[120,136],"an":[122],"exact":[123],"McNemar":[124],"test.":[125],"Replacing":[126],"80/20":[133],"increased":[135,196],"accuracy":[137],"by":[138,160,177,188,200],"3.19":[139],"4.52":[141],"percentage":[142],"points":[143],"across":[144],"backbones,":[146],"larger":[148],"change":[149],"than":[150,207,226],"any":[151],"module":[152,183,195],"produced.":[153],"Across":[154],"seeds,":[156],"SE":[157],"changed":[158],"macro-F1":[159],"+0.06":[161],"points,":[162],"within":[163],"seed-to-seed":[165],"range":[166],"unmodified":[169],"baseline,":[170],"whereas":[171],"ECA":[172],"SimAM":[174],"reduced":[175],"it":[176],"1.56":[178],"0.74":[180],"points.":[181],"No":[182],"improved":[184],"baseline":[187],"statistically":[190],"supported":[191],"margin,":[192],"yet":[193],"every":[194],"single-image":[197],"CPU":[198],"latency":[199],"4.3%":[201],"18.3%":[203],"while":[204],"adding":[205],"less":[206],"0.02%":[208],"floating-point":[210],"operations.":[211],"findings":[213],"show":[214],"that":[215],"evaluation":[217],"protocol":[218],"run-to-run":[220],"variance":[221],"affect":[222],"more":[225],"themselves,":[229],"reporting":[232],"checklist":[233],"is":[234],"proposed":[235],"future":[237],"evaluations":[238]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-03T00:00:00"}
