{"id":"https://openalex.org/W4412524685","doi":"https://doi.org/10.1145/3735014.3735882","title":"Deep Learning Techniques and Behavior Recognition in Video Image Sequence Analysis","display_name":"Deep Learning Techniques and Behavior Recognition in Video Image Sequence Analysis","publication_year":2024,"publication_date":"2024-12-13","ids":{"openalex":"https://openalex.org/W4412524685","doi":"https://doi.org/10.1145/3735014.3735882"},"language":"en","primary_location":{"id":"doi:10.1145/3735014.3735882","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3735014.3735882","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Big Data Mining and Information Processing","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":null,"display_name":"Dan Zeng","orcid":"https://orcid.org/0009-0005-2798-4526"},"institutions":[{"id":"https://openalex.org/I4210129465","display_name":"Wuhan Ship Development & Design Institute","ror":"https://ror.org/02mcdae06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129465"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dan Zeng","raw_affiliation_strings":["Wuhan Institute of Design and Sciences, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0009-0005-2798-4526","affiliations":[{"raw_affiliation_string":"Wuhan Institute of Design and Sciences, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4210129465"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210129465"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29772949,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"104","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9993000030517578,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9987000226974487,"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":0.7480623126029968},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6385297775268555},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5391820073127747},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5099128484725952},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4559725522994995},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.448383092880249},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4216892719268799}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7480623126029968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6385297775268555},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5391820073127747},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5099128484725952},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4559725522994995},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.448383092880249},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4216892719268799},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3735014.3735882","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3735014.3735882","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Big Data Mining and Information Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2766386834","https://openalex.org/W2784995342","https://openalex.org/W2794721028","https://openalex.org/W3080272091","https://openalex.org/W3116354579","https://openalex.org/W3124471630","https://openalex.org/W3138555712","https://openalex.org/W3184254438","https://openalex.org/W3214934779","https://openalex.org/W4212991200"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2804383999","https://openalex.org/W2802049774"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,34,44,68,83,92,105,119,124,143,150,154,163,168,177,182],"performance":[3],"bottleneck":[4],"of":[5,38,49,72,87,108,123,142,149,158,167,185],"distinguishing":[6],"complex":[7],"scenes":[8,172],"and":[9,43,51,77,128,133],"similar":[10,186],"actions":[11,187],"in":[12,28,74],"video":[13,75],"behavior":[14,114],"recognition,":[15],"a":[16,55,112,193],"hybrid":[17],"neural":[18,41],"network":[19,42],"architecture":[20],"based":[21],"on":[22,126],"spatio-temporal":[23,109,159],"feature":[24,57,93,196],"fusion":[25,94,197],"is":[26,60,64,79,100,137],"constructed":[27],"this":[29],"study.":[30],"By":[31],"organically":[32],"integrating":[33],"spatial":[35,69],"perception":[36],"advantages":[37],"3D":[39],"convolutional":[40],"time":[45,84],"series":[46,85],"modeling":[47],"capabilities":[48],"long-term":[50],"short-term":[52],"memory":[53],"networks,":[54],"double-stream":[56],"interaction":[58],"framework":[59],"innovatively":[61],"designed:":[62],"3D-CNN":[63],"used":[65,80],"to":[66,81,102],"analyze":[67],"topological":[70],"relationship":[71],"objects":[73],"frames,":[76],"LSTM":[78],"capture":[82],"law":[86],"cross-frame":[88],"motion":[89],"evolution.":[90],"In":[91],"stage,":[95],"an":[96],"attention":[97,178],"weighting":[98],"mechanism":[99,179],"introduced":[101],"dynamically":[103],"adjust":[104],"contribution":[106],"weight":[107],"features,":[110],"forming":[111],"multi-level":[113],"representation.":[115],"After":[116],"datasets":[117],"testing,":[118],"average":[120],"recognition":[121,164],"accuracy":[122],"model":[125,169],"UCF101":[127],"HMDB51":[129],"benchmarks":[130],"reaches":[131],"94.7%":[132],"72.3%,":[134],"respectively,":[135],"which":[136],"5.2%":[138],"higher":[139],"than":[140],"that":[141,153],"benchmark":[144],"method.":[145],"The":[146],"validation":[147],"experiment":[148],"module":[151],"shows":[152],"combined":[155],"training":[156],"strategy":[157],"features":[160],"can":[161,180],"reduce":[162],"error":[165],"rate":[166],"for":[170,199],"occluded":[171],"by":[173,188],"31%,":[174],"while":[175],"applying":[176],"improve":[181],"article":[183],"discrimination":[184],"19.8%.":[189],"This":[190],"study":[191],"provides":[192],"more":[194],"interpretable":[195],"paradigm":[198],"dynamic":[200],"visual":[201],"understanding.":[202]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
