{"id":"https://openalex.org/W7134891175","doi":"https://doi.org/10.1109/pcs65673.2025.11417629","title":"UNNIP: Memory Optimized Universal Neural Network Intra-Prediction for Custom On-Chip Hardware-Architectures","display_name":"UNNIP: Memory Optimized Universal Neural Network Intra-Prediction for Custom On-Chip Hardware-Architectures","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7134891175","doi":"https://doi.org/10.1109/pcs65673.2025.11417629"},"language":"en","primary_location":{"id":"doi:10.1109/pcs65673.2025.11417629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs65673.2025.11417629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Picture Coding Symposium (PCS)","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/A5085015365","display_name":"Viktor Herrmann","orcid":null},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Viktor Herrmann","raw_affiliation_strings":["Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute,Berlin,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute,Berlin,Germany","institution_ids":["https://openalex.org/I2800274787"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013006770","display_name":"Justin Knapheide","orcid":"https://orcid.org/0000-0003-3931-4288"},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Justin Knapheide","raw_affiliation_strings":["Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute,Berlin,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute,Berlin,Germany","institution_ids":["https://openalex.org/I2800274787"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038698717","display_name":"Benno Stabernack","orcid":"https://orcid.org/0000-0002-6654-1606"},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benno Stabernack","raw_affiliation_strings":["Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute,Berlin,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute,Berlin,Germany","institution_ids":["https://openalex.org/I2800274787"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800274787"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5174999833106995,"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":0.5174999833106995,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.06030000001192093,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T14347","display_name":"Big Data and Digital Economy","score":0.051899999380111694,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/artificial-neural-network","display_name":"Artificial neural network","score":0.5406000018119812},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.30149999260902405},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.274399995803833},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.2743000090122223},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.25360000133514404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6556000113487244},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5406000018119812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46230000257492065},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28700000047683716},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.25360000133514404},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2484000027179718},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.24400000274181366}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/pcs65673.2025.11417629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs65673.2025.11417629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"},{"id":"pmh:oai:publica.fraunhofer.de:publica/515118","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/515118","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2146395539","https://openalex.org/W2285660444","https://openalex.org/W2604319603","https://openalex.org/W2791741309","https://openalex.org/W2891736150","https://openalex.org/W2963003152","https://openalex.org/W2968469126","https://openalex.org/W3153617831","https://openalex.org/W3168354393","https://openalex.org/W3202918664"],"related_works":[],"abstract_inverted_index":{"Neural":[0],"network-based":[1],"intra":[2,45,78],"prediction":[3,10,79],"has":[4],"demonstrated":[5],"substantial":[6],"improvements":[7],"over":[8],"traditional":[9,123],"modes":[11],"from":[12],"block":[13],"based":[14],"hybrid":[15],"video":[16],"coding":[17],"frameworks":[18],"such":[19],"as":[20],"HEVC":[21],"and":[22,128,145],"VVC.":[23],"On":[24],"the":[25,27,40,66,69,113,132,153],"downside,":[26],"used":[28],"neural":[29,76],"networks":[30],"introduce":[31],"enormous":[32],"complexity":[33],"that":[34,81],"obstructs":[35],"efficient":[36],"hardware.":[37],"Due":[38],"to":[39,94,104,107,122,155],"inherent":[41],"sequential":[42],"structure":[43],"of":[44,49,68,102],"prediction,":[46],"this":[47],"category":[48],"tools":[50],"cannot":[51],"be":[52],"accelerated":[53],"with":[54,84],"off-chip":[55],"NPUs,":[56],"while":[57,131],"on-chip":[58,87],"integration":[59],"entails":[60],"high":[61],"area":[62],"costs":[63],"induced":[64],"by":[65,116,137],"memory-footprint":[67],"method.":[70],"This":[71,150],"paper":[72],"proposes":[73],"a":[74,96,156],"universal":[75],"network":[77],"model":[80,124],"is":[82],"co-designed":[83],"an":[85],"experimental":[86],"architecture.":[88],"The":[89],"method":[90,111],"leverages":[91],"tasklevel":[92],"redundancies":[93],"achieve":[95],"significantly":[97],"improved":[98],"tradeoff":[99],"in":[100],"terms":[101],"coding-gain":[103],"memory-footprint.":[105],"Compared":[106],"related":[108],"work,":[109],"our":[110],"reduces":[112],"overall":[114],"weight-parameters":[115],"\u00d7":[117],"4.38":[118],"-":[119,130],"near":[120],"orthogonal":[121],"optimization":[125,151],"like":[126],"pruning":[127],"quantization":[129],"BD-rate":[133],"also":[134],"slightly":[135],"improves":[136],"-0.":[138,146],"1":[139,142,147],"0":[140,148],"%(Y),-0.":[141],"4":[143],"%(U)":[144],"%(V).":[149],"enables":[152],"deployment":[154],"prototype":[157],"FPGA":[158],"implementation.":[159]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-12T00:00:00"}