{"id":"https://openalex.org/W2981005028","doi":"https://doi.org/10.1145/3340555.3355715","title":"Group-level Cohesion Prediction using Deep Learning Models with A Multi-stream Hybrid Network","display_name":"Group-level Cohesion Prediction using Deep Learning Models with A Multi-stream Hybrid Network","publication_year":2019,"publication_date":"2019-10-14","ids":{"openalex":"https://openalex.org/W2981005028","doi":"https://doi.org/10.1145/3340555.3355715","mag":"2981005028"},"language":"en","primary_location":{"id":"doi:10.1145/3340555.3355715","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340555.3355715","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Multimodal Interaction","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/A5048526869","display_name":"Tien Dang","orcid":"https://orcid.org/0000-0001-6894-2852"},"institutions":[{"id":"https://openalex.org/I4210092150","display_name":"Chonnam National University Hospital","ror":"https://ror.org/00f200z37","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I111277659","https://openalex.org/I4210092150"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Tien Xuan Dang","raw_affiliation_strings":["Chonnam National University"],"affiliations":[{"raw_affiliation_string":"Chonnam National University","institution_ids":["https://openalex.org/I4210092150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605822","display_name":"Soo-Hyung Kim","orcid":"https://orcid.org/0000-0003-3575-5035"},"institutions":[{"id":"https://openalex.org/I4210092150","display_name":"Chonnam National University Hospital","ror":"https://ror.org/00f200z37","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I111277659","https://openalex.org/I4210092150"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soo-Hyung Kim","raw_affiliation_strings":["Chonnam National University"],"affiliations":[{"raw_affiliation_string":"Chonnam National University","institution_ids":["https://openalex.org/I4210092150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087619194","display_name":"Hyung-Jeong Yang","orcid":"https://orcid.org/0000-0003-3024-5060"},"institutions":[{"id":"https://openalex.org/I4210092150","display_name":"Chonnam National University Hospital","ror":"https://ror.org/00f200z37","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I111277659","https://openalex.org/I4210092150"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyung-Jeong Yang","raw_affiliation_strings":["Chonnam National University"],"affiliations":[{"raw_affiliation_string":"Chonnam National University","institution_ids":["https://openalex.org/I4210092150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070936425","display_name":"Guee-Sang Lee","orcid":"https://orcid.org/0000-0002-8756-1382"},"institutions":[{"id":"https://openalex.org/I4210092150","display_name":"Chonnam National University Hospital","ror":"https://ror.org/00f200z37","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I111277659","https://openalex.org/I4210092150"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Guee-Sang Lee","raw_affiliation_strings":["Chonnam National University"],"affiliations":[{"raw_affiliation_string":"Chonnam National University","institution_ids":["https://openalex.org/I4210092150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072530242","display_name":"Hung Vo","orcid":"https://orcid.org/0000-0002-2910-1548"},"institutions":[{"id":"https://openalex.org/I4210092150","display_name":"Chonnam National University Hospital","ror":"https://ror.org/00f200z37","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I111277659","https://openalex.org/I4210092150"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Thanh-Hung Vo","raw_affiliation_strings":["Chonnam National University"],"affiliations":[{"raw_affiliation_string":"Chonnam National University","institution_ids":["https://openalex.org/I4210092150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5048526869"],"corresponding_institution_ids":["https://openalex.org/I4210092150"],"apc_list":null,"apc_paid":null,"fwci":1.0122,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.81019088,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"572","last_page":"576"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9854000210762024,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9854000210762024,"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/T11448","display_name":"Face recognition and analysis","score":0.9593999981880188,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9438999891281128,"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/cohesion","display_name":"Cohesion (chemistry)","score":0.7369241714477539},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.720871090888977},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193912863731384},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7041897177696228},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6209644079208374},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.615967333316803},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5376459360122681},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47475817799568176},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4728337228298187},{"id":"https://openalex.org/keywords/group-cohesiveness","display_name":"Group cohesiveness","score":0.43222254514694214},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42215797305107117},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12106451392173767},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09952190518379211}],"concepts":[{"id":"https://openalex.org/C104054115","wikidata":"https://www.wikidata.org/wiki/Q216828","display_name":"Cohesion (chemistry)","level":2,"score":0.7369241714477539},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.720871090888977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193912863731384},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7041897177696228},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6209644079208374},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.615967333316803},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5376459360122681},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47475817799568176},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4728337228298187},{"id":"https://openalex.org/C14641543","wikidata":"https://www.wikidata.org/wiki/Q553270","display_name":"Group cohesiveness","level":2,"score":0.43222254514694214},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42215797305107117},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12106451392173767},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09952190518379211},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340555.3355715","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340555.3355715","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Multimodal Interaction","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":22,"referenced_works":["https://openalex.org/W2094637479","https://openalex.org/W2108598243","https://openalex.org/W2143005665","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2559085405","https://openalex.org/W2745497104","https://openalex.org/W2767348466","https://openalex.org/W2821427990","https://openalex.org/W2889978276","https://openalex.org/W2894589512","https://openalex.org/W2894944581","https://openalex.org/W2895443688","https://openalex.org/W2963446712","https://openalex.org/W2963488642","https://openalex.org/W2963839617","https://openalex.org/W2963856926","https://openalex.org/W2964081807","https://openalex.org/W2964304707","https://openalex.org/W2964309882","https://openalex.org/W2980495289","https://openalex.org/W4234552385"],"related_works":["https://openalex.org/W1969135428","https://openalex.org/W3041605973","https://openalex.org/W2001372775","https://openalex.org/W2027585331","https://openalex.org/W2525246515","https://openalex.org/W1481039507","https://openalex.org/W2381411542","https://openalex.org/W1600779779","https://openalex.org/W3018574598","https://openalex.org/W1861963104"],"abstract_inverted_index":{"In":[0,41],"this":[1,45],"paper,":[2],"we":[3,47],"propose":[4],"a":[5,18],"hybrid":[6,85],"deep":[7],"learning":[8],"network":[9,86],"for":[10],"predicting":[11],"group":[12],"cohesion":[13],"in":[14,36,113],"images.":[15],"It":[16],"is":[17,26,35],"kind":[19],"of":[20,39,51],"regression":[21],"problem":[22],"and":[23,60,89,97],"its":[24],"objective":[25],"to":[27,43,79],"predict":[28],"the":[29,37,104,108,114],"Group":[30],"Cohesion":[31,110],"Score":[32],"(GCS),":[33],"which":[34],"range":[38],"[0,3].":[40],"order":[42],"solve":[44],"issue,":[46],"exploit":[48],"four":[49],"types":[50],"visual":[52],"cues,":[53],"such":[54],"as":[55],"scene,":[56],"skeleton,":[57],"UV":[58],"coordinates":[59],"face":[61],"image,":[62],"along":[63],"with":[64],"state-of-the-art":[65],"convolutional":[66],"neural":[67],"networks":[68],"(CNNs).":[69],"We":[70,101],"use":[71],"not":[72],"only":[73],"fusion":[74],"but":[75],"also":[76],"ensemble":[77],"methods":[78],"combine":[80],"these":[81],"approaches.":[82],"Our":[83],"proposed":[84],"achieves":[87],"0.517":[88],"0.416":[90],"mean":[91],"square":[92],"errors":[93],"(MSEs)":[94],"on":[95,107],"validation":[96],"testing":[98],"sets,":[99],"respectively.":[100],"finally":[102],"achieved":[103],"first":[105],"place":[106],"Group-level":[109],"Sub-challenge":[111],"(GC)":[112],"EmotiW":[115],"2019.":[116]},"counts_by_year":[{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}