{"id":"https://openalex.org/W2940187653","doi":"https://doi.org/10.1201/9780429507670-1","title":"Extreme Heterogeneity in Deep Learning Architectures","display_name":"Extreme Heterogeneity in Deep Learning Architectures","publication_year":2019,"publication_date":"2019-03-19","ids":{"openalex":"https://openalex.org/W2940187653","doi":"https://doi.org/10.1201/9780429507670-1","mag":"2940187653"},"language":"en","primary_location":{"id":"doi:10.1201/9780429507670-1","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9780429507670-1","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Smart Data","raw_type":"book-chapter"},"type":"book-chapter","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/A5103129194","display_name":"Jeff Anderson","orcid":"https://orcid.org/0000-0002-6210-1056"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jeff Anderson","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014196859","display_name":"Armin Mehrabian","orcid":"https://orcid.org/0000-0003-0587-9387"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Armin Mehrabian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101544860","display_name":"Jiaxin Peng","orcid":"https://orcid.org/0000-0002-2943-6305"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiaxin Peng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5001914825","display_name":"Tarek El\u2010Ghazawi","orcid":"https://orcid.org/0000-0001-9687-7939"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tarek El-Ghazawi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103129194"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7556,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.70147965,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9933000206947327,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9933000206947327,"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/T10320","display_name":"Neural Networks and Applications","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.4360945224761963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36254459619522095}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4360945224761963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36254459619522095}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1201/9780429507670-1","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9780429507670-1","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Smart Data","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2766143712"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2350741829","https://openalex.org/W2130043461","https://openalex.org/W2530322880"],"abstract_inverted_index":{"The":[0],"success":[1],"of":[2,11,21,57,90,109,145],"voice-activated":[3],"electronics":[4],"can":[5],"be":[6,47,80],"attributed":[7],"to":[8,18,46,79,103,116],"the":[9,19,107,117,130,141],"field":[10],"Machine":[12],"Learning":[13],"(ML),":[14],"and":[15,26,35,69,85,95,99,125,136],"more":[16],"specifically":[17],"development":[20],"Convolutional":[22],"Neural":[23,33,66,74],"Networks":[24,34,67],"(CNNs)":[25],"Deep":[27,32],"Learning.":[28],"This":[29],"chapter":[30],"reviews":[31],"advances":[36],"in":[37,52,148],"ML.":[38],"It":[39],"summarizes":[40],"hardware":[41],"architectures":[42],"that":[43],"are":[44,139],"likely":[45],"useful":[48],"for":[49,82],"NN":[50,60],"implementations":[51],"embedded":[53],"systems.":[54],"Different":[55],"types":[56,144],"NNs,":[58],"called":[59],"models,":[61],"such":[62],"as":[63],"CNNs,":[64],"Recurrent":[65],"(RNNs),":[68],"Long":[70],"Short-Term":[71],"Memory":[72],"(LSTM)":[73],"Networks,":[75],"have":[76,86],"been":[77],"shown":[78],"efficient":[81],"specific":[83],"classifications":[84],"their":[87],"own":[88],"sets":[89],"operations":[91,138,146],"with":[92],"diverse":[93],"computational":[94],"communication":[96],"requirements.":[97],"RNN":[98],"LSTM,":[100],"while":[101],"similar":[102],"a":[104,113,120],"CNN":[105],"from":[106],"standpoint":[108],"network":[110],"architecture,":[111],"introduce":[112],"time":[114],"dependency":[115],"network,":[118],"where":[119],"neuron\u2019s":[121],"output":[122],"is":[123],"stored":[124],"then":[126],"fed":[127],"back":[128],"into":[129],"neuron":[131],"during":[132],"subsequent":[133],"calculations.":[134],"Pooling":[135],"normalization":[137],"among":[140],"most":[142],"common":[143],"found":[147],"CNNs.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
