{"id":"https://openalex.org/W2962924844","doi":"https://doi.org/10.1109/globalsip.2016.7906042","title":"Dynamic scene classification using convolutional neural networks","display_name":"Dynamic scene classification using convolutional neural networks","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2962924844","doi":"https://doi.org/10.1109/globalsip.2016.7906042","mag":"2962924844"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2016.7906042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2016.7906042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","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/A5047750832","display_name":"Aalok Gangopadhyay","orcid":"https://orcid.org/0000-0002-1876-3140"},"institutions":[{"id":"https://openalex.org/I27674431","display_name":"Indian Institute of Technology Gandhinagar","ror":"https://ror.org/0036p5w23","country_code":"IN","type":"education","lineage":["https://openalex.org/I27674431"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aalok Gangopadhyay","raw_affiliation_strings":["Indian Institute of Technology Gandhinagar, Ahmedabad, Gujarat, IN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Gandhinagar, Ahmedabad, Gujarat, IN","institution_ids":["https://openalex.org/I27674431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103872058","display_name":"Shivam Mani Tripathi","orcid":null},"institutions":[{"id":"https://openalex.org/I27674431","display_name":"Indian Institute of Technology Gandhinagar","ror":"https://ror.org/0036p5w23","country_code":"IN","type":"education","lineage":["https://openalex.org/I27674431"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shivam Mani Tripathi","raw_affiliation_strings":["Indian Institute of Technology Gandhinagar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Gandhinagar","institution_ids":["https://openalex.org/I27674431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077046363","display_name":"Ishan Jindal","orcid":"https://orcid.org/0000-0002-8854-4189"},"institutions":[{"id":"https://openalex.org/I27674431","display_name":"Indian Institute of Technology Gandhinagar","ror":"https://ror.org/0036p5w23","country_code":"IN","type":"education","lineage":["https://openalex.org/I27674431"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ishan Jindal","raw_affiliation_strings":["Indian Institute of Technology Gandhinagar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Gandhinagar","institution_ids":["https://openalex.org/I27674431"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070142969","display_name":"Shanmuganathan Raman","orcid":"https://orcid.org/0000-0003-2718-7891"},"institutions":[{"id":"https://openalex.org/I27674431","display_name":"Indian Institute of Technology Gandhinagar","ror":"https://ror.org/0036p5w23","country_code":"IN","type":"education","lineage":["https://openalex.org/I27674431"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shanmuganathan Raman","raw_affiliation_strings":["Indian Institute of Technology Gandhinagar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Gandhinagar","institution_ids":["https://openalex.org/I27674431"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27674431"],"apc_list":null,"apc_paid":null,"fwci":1.859,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.90797334,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1255","last_page":"1259"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9994000196456909,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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":0.9987999796867371,"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":0.870281457901001},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7666903734207153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7087959051132202},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5289637446403503},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5288572907447815},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46900320053100586},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4560714364051819},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.43315213918685913},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3784651458263397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.870281457901001},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7666903734207153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7087959051132202},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5289637446403503},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5288572907447815},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46900320053100586},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4560714364051819},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.43315213918685913},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3784651458263397},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globalsip.2016.7906042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2016.7906042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","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":19,"referenced_works":["https://openalex.org/W1524680991","https://openalex.org/W1849277567","https://openalex.org/W2012592962","https://openalex.org/W2017814585","https://openalex.org/W2027922120","https://openalex.org/W2048790245","https://openalex.org/W2058879167","https://openalex.org/W2063492238","https://openalex.org/W2071524685","https://openalex.org/W2104978738","https://openalex.org/W2117539524","https://openalex.org/W2122476475","https://openalex.org/W2130913433","https://openalex.org/W2134670479","https://openalex.org/W2162915993","https://openalex.org/W2618530766","https://openalex.org/W2950094539","https://openalex.org/W3120421331","https://openalex.org/W4294375521"],"related_works":["https://openalex.org/W4391621807","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391621790","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W2788292821"],"abstract_inverted_index":{"The":[0,21,59,113],"task":[1],"of":[2,5,16,43,71,129,155,187],"classifying":[3],"videos":[4],"natural":[6],"dynamic":[7,123,169],"scenes":[8,124],"into":[9],"appropriate":[10],"classes":[11],"has":[12],"gained":[13],"a":[14,69,74,86],"lot":[15],"attention":[17],"in":[18,73,82],"recent":[19],"years.":[20],"problem":[22],"especially":[23],"becomes":[24],"challenging":[25],"when":[26],"the":[27,32,41,91,98,108,131,134,140,153,164,184,188],"camera":[28,135],"used":[29],"to":[30,55,84,120,182],"capture":[31],"video":[33,75],"is":[34,117,126,137],"dynamic.":[35],"In":[36],"this":[37,57,146],"paper,":[38],"we":[39],"analyse":[40],"performance":[42,154,186],"statistical":[44],"aggregation":[45,80,157],"(SA)":[46],"techniques":[47],"on":[48,152,173],"various":[49,156],"pre-trained":[50],"convolutional":[51],"neural":[52],"network(CNN)":[53],"models":[54],"address":[56],"problem.":[58],"proposed":[60,99,165,189],"approach":[61,100,166],"works":[62,106],"by":[63],"extracting":[64],"CNN":[65],"activation":[66],"features":[67],"for":[68,90,107],"number":[70],"frames":[72],"and":[76,110,125,139,159,180],"then":[77],"uses":[78],"an":[79,149],"scheme":[81],"order":[83],"obtain":[85],"robust":[87],"feature":[88],"descriptor":[89,115],"video.":[92],"We":[93,162],"show":[94],"through":[95],"results":[96],"that":[97],"performs":[101],"better":[102],"than":[103],"the-state-of-the":[104],"art":[105],"Maryland":[109,179],"YUPenn":[111,181],"dataset.":[112],"final":[114],"obtained":[116],"powerful":[118],"enough":[119],"distinguish":[121],"among":[122],"even":[127],"capable":[128],"addressing":[130],"scenario":[132],"where":[133],"motion":[136],"dominant":[138],"scene":[141,170],"dynamics":[142],"are":[143],"complex.":[144],"Further,":[145],"paper":[147],"shows":[148],"extensive":[150],"study":[151],"methods":[158],"their":[160],"combinations.":[161],"compare":[163],"with":[167],"other":[168],"classification":[171],"algorithms":[172],"two":[174],"publicly":[175],"available":[176],"datasets":[177],"\u2014":[178],"demonstrate":[183],"superior":[185],"approach.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}