{"id":"https://openalex.org/W7124914107","doi":"https://doi.org/10.1109/cloudcom67567.2025.11331355","title":"Multi-Modal Feature Fusion Distance Gating 3D Imaging Based on Edge Computing","display_name":"Multi-Modal Feature Fusion Distance Gating 3D Imaging Based on Edge Computing","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W7124914107","doi":"https://doi.org/10.1109/cloudcom67567.2025.11331355"},"language":null,"primary_location":{"id":"doi:10.1109/cloudcom67567.2025.11331355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloudcom67567.2025.11331355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 lEEE International Conference on Cloud Computing Technology and Science (CloudCom)","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/A5101566735","display_name":"Haojie Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haojie Huang","raw_affiliation_strings":["College of Computer Science, South-Central Minzu University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, South-Central Minzu University,Wuhan,China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050087857","display_name":"Bin Zhou","orcid":"https://orcid.org/0000-0001-5492-5816"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Zhou","raw_affiliation_strings":["College of Computer Science, South-Central Minzu University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, South-Central Minzu University,Wuhan,China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122847430","display_name":"Yuanai Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanai Xie","raw_affiliation_strings":["College of Computer Science, South-Central Minzu University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, South-Central Minzu University,Wuhan,China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014790039","display_name":"Pan Lai","orcid":"https://orcid.org/0000-0002-4967-5573"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pan Lai","raw_affiliation_strings":["College of Computer Science, South-Central Minzu University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, South-Central Minzu University,Wuhan,China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123436999","display_name":"Xiao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Zhang","raw_affiliation_strings":["College of Computer Science, South-Central Minzu University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, South-Central Minzu University,Wuhan,China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101646674","display_name":"Jiwei Zhu","orcid":"https://orcid.org/0009-0000-8675-9795"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianlin Zhu","raw_affiliation_strings":["College of Computer Science, South-Central Minzu University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, South-Central Minzu University,Wuhan,China","institution_ids":["https://openalex.org/I145897649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101566735"],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.69586675,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.7508999705314636,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.7508999705314636,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.05270000174641609,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.05139999836683273,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5346999764442444},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4902999997138977},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.47780001163482666},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44290000200271606},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.4223000109195709},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4146000146865845},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.38989999890327454},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3538999855518341},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.3465999960899353}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7591000199317932},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7361999750137329},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5358999967575073},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5346999764442444},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4902999997138977},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.47780001163482666},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.4223000109195709},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4146000146865845},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38989999890327454},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.27300000190734863},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.26429998874664307},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cloudcom67567.2025.11331355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloudcom67567.2025.11331355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 lEEE International Conference on Cloud Computing Technology and Science (CloudCom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3618258879","display_name":null,"funder_award_id":"CZY23006","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2024235615","https://openalex.org/W2041576007","https://openalex.org/W2963925437","https://openalex.org/W2981715392","https://openalex.org/W2982470081","https://openalex.org/W2985775862","https://openalex.org/W3034543232","https://openalex.org/W3034604951","https://openalex.org/W3138516171","https://openalex.org/W3159481202","https://openalex.org/W3171125843","https://openalex.org/W3173727695","https://openalex.org/W4206706211","https://openalex.org/W4213019189","https://openalex.org/W4214520160","https://openalex.org/W4224282157","https://openalex.org/W4312468718","https://openalex.org/W4322769471","https://openalex.org/W4385245566","https://openalex.org/W4387638628","https://openalex.org/W4390873354","https://openalex.org/W4390874575","https://openalex.org/W4401024837","https://openalex.org/W4403599575","https://openalex.org/W4407453584"],"related_works":[],"abstract_inverted_index":{"3D":[0,67,251,261],"Range-Gated":[1],"Imaging":[2],"technology":[3],"is":[4,165,197],"widely":[5],"used":[6],"for":[7,249,259,264],"detection":[8],"in":[9,44,237],"complex":[10,265],"environments":[11],"(such":[12],"as":[13],"autonomous":[14],"driving":[15],"scenarios)":[16],"due":[17],"to":[18,110,152,229],"its":[19,24],"excellent":[20],"anti-interference":[21],"capabilities.":[22],"However,":[23],"application":[25],"faces":[26],"the":[27,37,51,76,101,111,129,148,169,175,181,211,215],"dual":[28,80],"challenges":[29],"of":[30,33,40,55,133,150,171,185],"a":[31,66,79,157,220,245],"lack":[32],"specialized":[34],"datasets":[35],"and":[36,53,131,174,194,239,253,256],"limited":[38],"performance":[39,236],"traditional":[41],"RGB":[42,98],"models":[43,263],"low":[45],"signal-to-noise":[46],"ratio":[47],"environments,":[48],"which":[49],"hinders":[50],"transfer":[52],"generalization":[54,177],"deep":[56],"learning":[57],"methods.":[58],"To":[59,146,179],"address":[60,180],"these":[61],"difficulties,":[62],"this":[63],"paper":[64],"proposes":[65],"imaging":[68,262],"method":[69,213],"based":[70],"on":[71,95,143,219],"multimodal":[72],"feature":[73,122,202],"fusion.":[74],"Specifically,":[75],"model":[77],"adopts":[78],"Vision":[81],"Transformer":[82],"(ViT)":[83],"encoder,":[84],"single-decoder":[85],"architecture.":[86],"On":[87,100],"one":[88],"hand,":[89,103],"it":[90,104,118,127,137],"performs":[91],"pre-trained":[92],"ViT":[93,108],"encoding":[94,109],"geometrically":[96],"re-projected":[97],"images.":[99,113],"other":[102],"applies":[105],"an":[106,187],"isomorphic":[107],"range-gated":[112],"Through":[114],"layer-wise":[115],"semantic":[116],"recombination,":[117],"achieves":[119],"efficient":[120,205],"cross-modal":[121,250],"fusion,":[123],"not":[124],"only":[125],"does":[126],"enhance":[128],"robustness":[130],"accuracy":[132],"depth":[134,216],"estimation,":[135],"but":[136],"can":[138],"also":[139],"be":[140],"easily":[141],"deployed":[142],"edge":[144],"devices.":[145],"overcome":[147],"problem":[149],"overfitting":[151],"LiDAR":[153],"ground":[154],"truth":[155],"data,":[156],"spatially":[158],"constrained":[159],"window":[160],"cropping":[161],"data":[162],"augmentation":[163],"strategy":[164],"designed,":[166],"significantly":[167],"increasing":[168],"diversity":[170],"training":[172,193],"samples":[173],"model's":[176],"ability.":[178],"input":[182],"resolution":[183],"limitations":[184],"Transformers,":[186],"optimization":[188],"scheme":[189],"combining":[190],"dynamic":[191],"patch-based":[192],"progressive":[195],"up-sampling":[196],"further":[198],"proposed,":[199],"balancing":[200],"high-resolution":[201],"representation":[203],"with":[204,233],"training.":[206],"Experimental":[207],"results":[208],"show":[209],"that":[210],"proposed":[212],"reduces":[214],"estimation":[217],"RMSE":[218],"public":[221],"test":[222],"set":[223],"by":[224],"more":[225],"than":[226],"12%":[227],"compared":[228],"mainstream":[230],"baseline":[231],"models,":[232],"particularly":[234],"outstanding":[235],"low-texture":[238],"long-distance":[240],"scenes.":[241],"This":[242],"research":[243],"provides":[244],"systematic":[246],"technical":[247],"solution":[248],"perception":[252],"offers":[254],"theoretical":[255],"engineering":[257],"references":[258],"designing":[260],"environments.":[266]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-21T00:00:00"}
