{"id":"https://openalex.org/W7124835295","doi":"https://doi.org/10.1109/cloudcom67567.2025.11331312","title":"Sparse Manifold Retrieval Network for ICESat-2 Photon Point Cloud Denoising","display_name":"Sparse Manifold Retrieval Network for ICESat-2 Photon Point Cloud Denoising","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W7124835295","doi":"https://doi.org/10.1109/cloudcom67567.2025.11331312"},"language":null,"primary_location":{"id":"doi:10.1109/cloudcom67567.2025.11331312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloudcom67567.2025.11331312","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/A5032620407","display_name":"Hengming Dai","orcid":"https://orcid.org/0000-0002-8206-5902"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hengming Dai","raw_affiliation_strings":["Institute of International Rivers and Eco-Security, Yunnan University,Kunming,China,650500"],"affiliations":[{"raw_affiliation_string":"Institute of International Rivers and Eco-Security, Yunnan University,Kunming,China,650500","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068512767","display_name":"Haihan Duan","orcid":"https://orcid.org/0000-0001-6438-3790"},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haihan Duan","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123389020","display_name":"Cong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Zhang","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123435003","display_name":"Yang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088100","display_name":"Stellar Science (United States)","ror":"https://ror.org/00171m316","country_code":"US","type":"company","lineage":["https://openalex.org/I4210088100"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Zhou","raw_affiliation_strings":["Nova Stella (Shenzhen) Technology Co., Ltd.,China"],"affiliations":[{"raw_affiliation_string":"Nova Stella (Shenzhen) Technology Co., Ltd.,China","institution_ids":["https://openalex.org/I4210088100"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123382962","display_name":"Xiaoyi Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyi Fan","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123386631","display_name":"Zhifang Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhifang Zhao","raw_affiliation_strings":["Institute of International Rivers and Eco-Security, Yunnan University,Kunming,China,650500"],"affiliations":[{"raw_affiliation_string":"Institute of International Rivers and Eco-Security, Yunnan University,Kunming,China,650500","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5032620407"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.62397313,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.2953000068664551,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.2953000068664551,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.17229999601840973,"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"}},{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.08550000190734863,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6480000019073486},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6394000053405762},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.5787000060081482},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5307999849319458},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5198000073432922},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4997999966144562},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.46549999713897705},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.43939998745918274}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6818000078201294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.673799991607666},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6480000019073486},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6394000053405762},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.5787000060081482},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5307999849319458},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5198000073432922},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4997999966144562},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.46549999713897705},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.43939998745918274},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4381999969482422},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4171999990940094},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3440000116825104},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3416999876499176},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.27950000762939453},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2605000138282776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cloudcom67567.2025.11331312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloudcom67567.2025.11331312","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":[{"display_name":"Life below water","score":0.8261973261833191,"id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2211722331","https://openalex.org/W2556802233","https://openalex.org/W2568967893","https://openalex.org/W2737234477","https://openalex.org/W2792703975","https://openalex.org/W2963125977","https://openalex.org/W2963182550","https://openalex.org/W3037823952","https://openalex.org/W3119827121","https://openalex.org/W3133474646","https://openalex.org/W3149173575","https://openalex.org/W3210787280","https://openalex.org/W4225349165","https://openalex.org/W4243622766","https://openalex.org/W4285060714","https://openalex.org/W4308739658","https://openalex.org/W4321484970","https://openalex.org/W4386065742","https://openalex.org/W4386075910","https://openalex.org/W4389369158","https://openalex.org/W4390587028","https://openalex.org/W4402673231","https://openalex.org/W4413190394"],"related_works":[],"abstract_inverted_index":{"The":[0,153],"photon":[1,82],"point":[2],"clouds":[3],"acquired":[4],"by":[5,17],"ICESat-2/ATLAS":[6],"offer":[7],"unprecedented":[8],"potential":[9],"for":[10,24,80],"Earth":[11],"observation":[12],"but":[13],"are":[14],"heavily":[15],"contaminated":[16],"noise":[18],"photons,":[19],"posing":[20],"a":[21,49,75,92,112,129],"significant":[22],"challenge":[23],"downstream":[25],"applications.":[26],"Traditional":[27],"denoising":[28,145,162],"methods,":[29],"which":[30],"often":[31,54],"rely":[32],"on":[33,128],"local":[34],"density":[35],"statistics,":[36],"struggle":[37],"with":[38,168],"complex":[39],"terrains":[40],"and":[41,111,147,171],"varying":[42],"signal-to-noise":[43],"ratios.":[44],"While":[45],"deep":[46,77],"learning":[47,78],"presents":[48],"promising":[50],"alternative,":[51],"existing":[52],"approaches":[53],"inefficiently":[55],"process":[56],"the":[57,99,125,156],"inherently":[58],"sparse":[59,109,169],"data":[60],"via":[61],"2D":[62],"projections":[63],"or":[64],"non-optimized":[65],"3D":[66],"networks.":[67],"To":[68],"address":[69],"these":[70],"limitations,":[71],"this":[72],"paper":[73],"introduces":[74],"novel":[76],"framework":[79],"ICESat-2":[81],"denoising,":[83],"termed":[84],"Sparse":[85],"Manifold":[86],"Retrieval":[87],"Network":[88],"(SMRNet).":[89],"We":[90],"propose":[91],"Manifold-Aware":[93],"Convolution":[94],"(MAC)":[95],"module":[96,117],"to":[97,118],"capture":[98],"continuous":[100],"manifold":[101],"structures":[102],"of":[103,137,158],"signal":[104],"photons":[105],"through":[106],"multi-scale":[107],"dilated":[108],"convolutions,":[110],"Cross-Scale":[113],"Pyramid":[114],"Enhancement":[115],"(CSPE)":[116],"effectively":[119],"refine":[120],"multi-level":[121],"features":[122],"extracted":[123],"from":[124],"encoder.":[126],"Evaluated":[127],"manually":[130],"annotated":[131],"dataset":[132],"covering":[133],"southeastern":[134],"coastal":[135],"regions":[136],"China,":[138],"SMRNet":[139,159],"demonstrates":[140],"superior":[141],"performance":[142],"over":[143],"traditional":[144],"method":[146],"data-driven":[148],"baselines":[149],"across":[150],"multiple":[151],"metrics.":[152],"results":[154],"underscore":[155],"effectiveness":[157],"in":[160,165],"enhancing":[161],"accuracy,":[163],"particularly":[164],"challenging":[166],"environments":[167],"signals":[170],"rugged":[172],"topography.":[173]},"counts_by_year":[],"updated_date":"2026-01-22T23:29:09.771500","created_date":"2026-01-21T00:00:00"}