{"id":"https://openalex.org/W2761745809","doi":"https://doi.org/10.1145/3133264.3133276","title":"Vegetation Recognition based on Deep Learning with Feature Fusion","display_name":"Vegetation Recognition based on Deep Learning with Feature Fusion","publication_year":2017,"publication_date":"2017-08-25","ids":{"openalex":"https://openalex.org/W2761745809","doi":"https://doi.org/10.1145/3133264.3133276","mag":"2761745809"},"language":"en","primary_location":{"id":"doi:10.1145/3133264.3133276","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3133264.3133276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Advances in Image Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102608449","display_name":"Shuai Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210086028","display_name":"Technology and Engineering Center for Space Utilization","ror":"https://ror.org/00cn03n83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210086028"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Fan","raw_affiliation_strings":["Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210086028","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339270","display_name":"Ye Li","orcid":"https://orcid.org/0000-0003-1303-7219"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210086028","display_name":"Technology and Engineering Center for Space Utilization","ror":"https://ror.org/00cn03n83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210086028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Li","raw_affiliation_strings":["Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210086028","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114950142","display_name":"Yan Zhen","orcid":"https://orcid.org/0009-0007-8461-2539"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210086028","display_name":"Technology and Engineering Center for Space Utilization","ror":"https://ror.org/00cn03n83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210086028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Yan","raw_affiliation_strings":["Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210086028","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064138796","display_name":"Lili Guo","orcid":"https://orcid.org/0000-0002-0470-692X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210086028","display_name":"Technology and Engineering Center for Space Utilization","ror":"https://ror.org/00cn03n83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210086028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lili Guo","raw_affiliation_strings":["Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210086028","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077189077","display_name":"Xianfeng Wang","orcid":"https://orcid.org/0000-0002-8614-5627"},"institutions":[{"id":"https://openalex.org/I4210086028","display_name":"Technology and Engineering Center for Space Utilization","ror":"https://ror.org/00cn03n83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210086028"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianfeng Wang","raw_affiliation_strings":["Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210086028","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9850000143051147,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9688000082969666,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.6746224164962769},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.655342698097229},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6389593482017517},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5688904523849487},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5220113396644592},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4824395775794983},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4716412425041199},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4454265832901001}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6746224164962769},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.655342698097229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6389593482017517},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5688904523849487},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5220113396644592},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4824395775794983},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4716412425041199},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4454265832901001},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3133264.3133276","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3133264.3133276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Advances in Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1617962234","https://openalex.org/W2063113990","https://openalex.org/W2291068538","https://openalex.org/W2314029052","https://openalex.org/W2395611524","https://openalex.org/W2480078828","https://openalex.org/W2484692031","https://openalex.org/W2494341560","https://openalex.org/W2512351403","https://openalex.org/W2530530432","https://openalex.org/W2538244214","https://openalex.org/W2553205900","https://openalex.org/W2577537809","https://openalex.org/W2588561483","https://openalex.org/W3105097574","https://openalex.org/W3105127913","https://openalex.org/W4248710273"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2804383999","https://openalex.org/W2802049774"],"abstract_inverted_index":{"Vegetation":[0],"recognition":[1,68,103,157,209],"is":[2,43,116,180],"an":[3],"important":[4],"task":[5],"for":[6,17,66,146],"optical":[7,55,89,127,212],"remote":[8,56,90,128,213],"sensing":[9,57,91,129,214],"image":[10],"parsing,":[11],"providing":[12],"information":[13],"on":[14,106],"vegetation":[15,52,67,74,85,102,147,160,168,184,208],"cover":[16],"disaster":[18],"monitoring,":[19,23],"natural":[20],"environment":[21],"change":[22],"etc.":[24],"In":[25,186],"recent":[26],"years,":[27],"deep":[28,46,108,140],"learning":[29,47],"methods":[30,61],"have":[31],"driven":[32],"a":[33,44,101,107,139,143,189,193],"great":[34],"advance":[35],"in":[36,118],"object":[37],"recognition.":[38,148],"Convolutional":[39],"neural":[40],"network":[41,111],"(CNN)":[42],"typical":[45],"method":[48,104,204],"which":[49],"can":[50],"recognize":[51],"objects":[53,86,169],"from":[54,87,126,138,161,210],"images.":[58,163,215],"However,":[59],"CNN":[60],"exploit":[62],"only":[63],"high-level":[64,134],"features":[65,125,137],"and":[69,76,131,135,142,177,192],"do":[70],"not":[71],"consider":[72],"multi-scale":[73,183],"objects,":[75],"thus":[77,178],"cannot":[78],"achieve":[79],"high-accuracy":[80,206],"pixel-wise":[81,207],"semantic":[82],"segmentation":[83],"of":[84,151,154,159],"complex":[88,162,211],"images":[92],"at":[93],"various":[94,171],"resolutions.":[95],"To":[96],"deal":[97],"with":[98,112,170],"these":[99],"problems,":[100],"based":[105],"fully":[109],"convolutional":[110],"feature":[113,155],"fusion":[114,150],"(FCN-FF)":[115],"proposed":[117],"this":[119,187],"paper.":[120],"The":[121,149,198],"FCN-FF":[122,166],"extracts":[123],"hierarchical":[124],"images,":[130],"then":[132],"fuses":[133],"low-level":[136],"layer":[141,145],"shallow":[144],"different":[152],"levels":[153],"improves":[156],"accuracy":[158],"Furthermore,":[164],"the":[165],"selects":[167],"spatial":[172],"resolutions":[173],"as":[174],"training":[175],"samples":[176],"it":[179],"suitable":[181],"to":[182],"objects.":[185],"study,":[188],"validation":[190],"experiment":[191,195],"comparative":[194],"are":[196],"performed.":[197],"experimental":[199],"results":[200],"show":[201],"that":[202],"our":[203],"achieves":[205]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
