{"id":"https://openalex.org/W4391406984","doi":"https://doi.org/10.1109/tmm.2024.3360689","title":"Learnable Tensor Graph Fusion Framework for Natural Image Segmentation","display_name":"Learnable Tensor Graph Fusion Framework for Natural Image Segmentation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4391406984","doi":"https://doi.org/10.1109/tmm.2024.3360689"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2024.3360689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2024.3360689","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","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/A5100408524","display_name":"Xiaoqian Zhang","orcid":"https://orcid.org/0000-0002-4007-4501"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqian Zhang","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":"https://orcid.org/0000-0002-4007-4501","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101720734","display_name":"Chao Luo","orcid":"https://orcid.org/0009-0001-1412-9548"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Luo","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":"https://orcid.org/0009-0001-1412-9548","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112719601","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0002-0008-0659"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100702878","display_name":"Jinghao Li","orcid":"https://orcid.org/0000-0002-9122-7184"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghao Li","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103246366","display_name":"Shuai Zhao","orcid":"https://orcid.org/0000-0002-0051-5157"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Zhao","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":"https://orcid.org/0000-0002-0051-5157","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067467767","display_name":"Daojian Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I2801345734","display_name":"China Academy of Engineering Physics","ror":"https://ror.org/039vqpp67","country_code":"CN","type":"facility","lineage":["https://openalex.org/I2801345734"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daojian Jiang","raw_affiliation_strings":["Institute of Chemical Materials, China Academy of Engineering Physics, Mianyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Chemical Materials, China Academy of Engineering Physics, Mianyang, China","institution_ids":["https://openalex.org/I2801345734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0219,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7508733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"26","issue":null,"first_page":"7160","last_page":"7173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9948999881744385,"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":0.9948999881744385,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9921000003814697,"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/computer-science","display_name":"Computer science","score":0.7336885929107666},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5959053039550781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5383933782577515},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44101250171661377},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4381105899810791},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4094350039958954},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.40885311365127563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3858007788658142}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7336885929107666},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5959053039550781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5383933782577515},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44101250171661377},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4381105899810791},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4094350039958954},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.40885311365127563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3858007788658142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2024.3360689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2024.3360689","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2669201131","display_name":null,"funder_award_id":"2022NSFSC0839","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"},{"id":"https://openalex.org/G4257343781","display_name":null,"funder_award_id":"62102331","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W201974436","https://openalex.org/W1669104078","https://openalex.org/W1901129140","https://openalex.org/W1907775068","https://openalex.org/W1923697677","https://openalex.org/W1975172027","https://openalex.org/W1981458038","https://openalex.org/W1993962865","https://openalex.org/W2043571470","https://openalex.org/W2087714402","https://openalex.org/W2119300483","https://openalex.org/W2124260943","https://openalex.org/W2125637308","https://openalex.org/W2197707282","https://openalex.org/W2199534117","https://openalex.org/W2338572068","https://openalex.org/W2565835729","https://openalex.org/W2618530766","https://openalex.org/W2751449619","https://openalex.org/W2765811365","https://openalex.org/W2921065608","https://openalex.org/W2927689530","https://openalex.org/W2949579163","https://openalex.org/W2952420591","https://openalex.org/W2964137015","https://openalex.org/W2973099107","https://openalex.org/W2998004380","https://openalex.org/W2998358581","https://openalex.org/W3044063956","https://openalex.org/W3080113507","https://openalex.org/W3083779147","https://openalex.org/W3102894800","https://openalex.org/W3121736262","https://openalex.org/W3160287418","https://openalex.org/W3168468320","https://openalex.org/W3208516906","https://openalex.org/W3209159014","https://openalex.org/W4200185184","https://openalex.org/W4226265242","https://openalex.org/W4236137412","https://openalex.org/W4239510810","https://openalex.org/W4296337774","https://openalex.org/W4360753265","https://openalex.org/W4387968004","https://openalex.org/W4390190093","https://openalex.org/W6640295612","https://openalex.org/W6714133674","https://openalex.org/W6743484365"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W2371519352","https://openalex.org/W4205800335","https://openalex.org/W2386644571","https://openalex.org/W2551987074","https://openalex.org/W2372421320"],"abstract_inverted_index":{"Existing":[0],"natural":[1,40,132,141],"image":[2,41,142],"segmentation":[3,42,130,143,158],"tasks":[4],"often":[5],"face":[6],"some":[7,166],"troubles":[8],"in":[9,46],"getting":[10],"accurate":[11],"contours":[12],"or":[13],"causing":[14],"over-segmentation":[15],"of":[16,26,93,105,131,145,160],"local":[17],"areas":[18],"during":[19],"segmentation,":[20],"and":[21,61,122,140],"the":[22,52,62,67,74,90,94,106,116,129,146,152,157],"multi-feature":[23,63,68,95,107],"information":[24,72,96,108],"mining":[25],"images":[27,54],"is":[28,44,65,120,163],"insufficient.":[29],"To":[30],"address":[31],"these":[32],"problems,":[33],"learnable":[34],"tensor":[35,82],"graph":[36,84,113,119,137],"fusion":[37,85],"framework":[38,162],"for":[39],"(LTGF-NIS)":[43],"proposed":[45,147],"this":[47],"paper.":[48],"Firstly,":[49],"we":[50,77],"pre-process":[51],"original":[53],"by":[55,97,109],"adaptive":[56,80,111],"morphological":[57],"reconstruction":[58],"watershed":[59],"transform,":[60],"data":[64,69,154],"extracted,":[66],"matrix":[70],"contains":[71],"about":[73],"image.":[75],"Then":[76],"design":[78],"an":[79],"weighted":[81,112],"affinity":[83,118,136],"method":[86],"(AWTAGF),":[87],"which":[88],"learns":[89],"higher-order":[91],"correlation":[92],"two":[98],"coupling":[99],"tensor,":[100],"while":[101],"achieving":[102],"consistent":[103],"representation":[104],"using":[110,124],"fusion.":[114],"Finally,":[115],"obtained":[117],"clustered":[121],"segmented":[123],"spectral":[125],"clustering":[126],"to":[127,165],"realize":[128],"images.":[133],"We":[134],"test":[135],"learning":[138],"ability":[139],"effect":[144,159],"algorithm":[148],"on":[149],"several":[150],"datasets,":[151],"experimental":[153],"indicates":[155],"that":[156],"our":[161],"superior":[164],"existing":[167],"advanced":[168],"methods.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}