{"id":"https://openalex.org/W7147543642","doi":"https://doi.org/10.1109/cnml68938.2026.11453044","title":"Eye-Tracking Fixation Duration-Weighted Natural Image Region of Interest (ROI) Segmentation System","display_name":"Eye-Tracking Fixation Duration-Weighted Natural Image Region of Interest (ROI) Segmentation System","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147543642","doi":"https://doi.org/10.1109/cnml68938.2026.11453044"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11453044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","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/A5100608484","display_name":"Bo Jiang","orcid":"https://orcid.org/0000-0003-0530-2860"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Jiang","raw_affiliation_strings":["Chongqing University of Technology,College of Electrical and Electronic Engineering,China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Technology,College of Electrical and Electronic Engineering,China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088548970","display_name":"Jie Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Huang","raw_affiliation_strings":["Chongqing University of Technology,College of Electrical and Electronic Engineering,China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Technology,College of Electrical and Electronic Engineering,China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132702639","display_name":"Fan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["Chongqing University of Technology,College of Electrical and Electronic Engineering,China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Technology,College of Electrical and Electronic Engineering,China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132708217","display_name":"Feng Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wen","raw_affiliation_strings":["Chongqing University of Technology,College of Electrical and Electronic Engineering,China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Technology,College of Electrical and Electronic Engineering,China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109375493","display_name":"Shen Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shen Xiao","raw_affiliation_strings":["Chongqing University of Technology,College of Electrical and Electronic Engineering,China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Technology,College of Electrical and Electronic Engineering,China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5132614098","display_name":"Jing Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Huang","raw_affiliation_strings":["Chongqing University of Technology,College of Electrical and Electronic Engineering,China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Technology,College of Electrical and Electronic Engineering,China","institution_ids":["https://openalex.org/I50632499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100608484"],"corresponding_institution_ids":["https://openalex.org/I50632499"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.92081475,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"745","last_page":"749"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.8733000159263611,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.8733000159263611,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.09179999679327011,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.0027000000700354576,"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/segmentation","display_name":"Segmentation","score":0.7261000275611877},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5680999755859375},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.5414999723434448},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.487199991941452},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.48249998688697815},{"id":"https://openalex.org/keywords/fixation","display_name":"Fixation (population genetics)","score":0.4657000005245209},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.38769999146461487},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.3792000114917755}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7700999975204468},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7261000275611877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7242000102996826},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6453999876976013},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5680999755859375},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.48249998688697815},{"id":"https://openalex.org/C146249460","wikidata":"https://www.wikidata.org/wiki/Q2914991","display_name":"Fixation (population genetics)","level":3,"score":0.4657000005245209},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.38769999146461487},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3792000114917755},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.3783000111579895},{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.357699990272522},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.3061000108718872},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.2727000117301941},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2696000039577484},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11453044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2013112874","https://openalex.org/W2103666701","https://openalex.org/W2128272608","https://openalex.org/W2136704614","https://openalex.org/W2150066425","https://openalex.org/W2151103935","https://openalex.org/W2165835468"],"related_works":[],"abstract_inverted_index":{"Region":[0],"of":[1,38,45,119,138,155,173],"Interest":[2],"(ROI)":[3],"segmentation":[4,53,70,101],"is":[5,102,153],"a":[6,66,105,129,149],"core":[7],"technology":[8],"for":[9,72,108],"image":[10,23],"semantic":[11,94],"understanding":[12],"and":[13,27,40,55,89,92,170],"visual":[14,36,47],"attention":[15,57],"analysis,":[16],"widely":[17],"applied":[18],"in":[19,50],"fields":[20],"such":[21],"as":[22,142],"retrieval,":[24],"advertising":[25],"design,":[26],"autonomous":[28],"driving":[29],"perception.":[30],"Traditional":[31],"methods":[32],"rely":[33],"on":[34,123],"low-level":[35],"features":[37,95],"images":[39],"ignore":[41],"the":[42,116,120,134,139,143,167,174],"subjective":[43],"orientation":[44],"human":[46],"attention,":[48],"resulting":[49],"deviations":[51],"between":[52],"results":[54],"actual":[56],"regions.":[58],"To":[59],"address":[60],"this":[61,63,126],"issue,":[62],"paper":[64,127],"proposes":[65,128],"fixation":[67,86,135],"duration-weighted":[68,136],"ROI":[69,110,163],"system":[71,122],"natural":[73],"images.":[74],"By":[75],"collecting":[76],"eye-tracking":[77,124,156,161],"data":[78],"to":[79,113,147],"extract":[80],"key":[81],"parameters,":[82],"constructing":[83],"heatmaps":[84,137],"through":[85,115],"point":[87],"clustering":[88],"duration":[90],"weighting,":[91],"integrating":[93],"with":[96],"adaptive":[97],"threshold":[98],"segmentation,":[99,164],"high-precision":[100],"achieved,":[103],"providing":[104],"new":[106],"solution":[107],"intelligent":[109],"segmentation.":[111],"Furthermore,":[112],"break":[114],"dependence":[117],"constraint":[118],"original":[121],"data,":[125],"subsequent":[130],"optimization":[131],"scheme:":[132],"using":[133],"Toronto":[140],"dataset":[141],"supervisory":[144],"ground":[145],"truth":[146],"train":[148],"deep":[150],"network":[151],"that":[152],"independent":[154],"data.":[157],"This":[158],"scheme":[159],"enables":[160],"hardware-free":[162],"greatly":[165],"enhancing":[166],"deployment":[168],"value":[169],"application":[171],"scope":[172],"research":[175],"results.":[176]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}