乐胖代购免代理版

{"id":"https://openalex.org/W2775119854","doi":"https://doi.org/10.1109/ecai.2017.8166501","title":"CPU and GPU gray scale image conversion on mobile platforms","display_name":"CPU and GPU gray scale image conversion on mobile platforms","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2775119854","doi":"https://doi.org/10.1109/ecai.2017.8166501","mag":"2775119854"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecai.2017.8166501","pdf_url":null,"source":{"id":"https://openalex.org/S4363608455","display_name":"2022 14th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5032196187","display_name":"Valeriu Manuel Ionescu","orcid":"https://orcid.org/0000-0003-2641-1599"},"institutions":[{"id":"https://openalex.org/I185286233","display_name":"University of Pitesti","ror":"https://ror.org/058b16x44","country_code":"RO","type":"education","lineage":["https://openalex.org/I185286233"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Valeriu Manuel Ionescu","raw_affiliation_strings":["Department of Electronics, Communications and Computers University of Pitesti, Pitesti, Romania"],"affiliations":[{"raw_affiliation_string":"Department of Electronics, Communications and Computers University of Pitesti, Pitesti, Romania","institution_ids":["https://openalex.org/I185286233"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5032196187"],"corresponding_institution_ids":["https://openalex.org/I185286233"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":2,"citation_normalized_percentile":{"value":0.329819,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":71,"max":75},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9981,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9981,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.995,"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":0.9933,"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":[],"concepts":[{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.9265648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8342869},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.52521306},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5079513},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5034806},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48857912},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46137914},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.43558496},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3958581},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.28244197},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecai.2017.8166501","pdf_url":null,"source":{"id":"https://openalex.org/S4363608455","display_name":"2022 14th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.87,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":8,"referenced_works":["https://openalex.org/W136594790","https://openalex.org/W145048580","https://openalex.org/W1565147430","https://openalex.org/W164384110","https://openalex.org/W1916086637","https://openalex.org/W2109507849","https://openalex.org/W2122078011","https://openalex.org/W2553454427"],"related_works":["https://openalex.org/W4362659915","https://openalex.org/W2972861887","https://openalex.org/W2768918307","https://openalex.org/W2393930098","https://openalex.org/W2321543601","https://openalex.org/W2113071088","https://openalex.org/W2110031805","https://openalex.org/W2040020606","https://openalex.org/W1990016983","https://openalex.org/W115686965"],"abstract_inverted_index":{"In":[0],"image":[1,86],"processing,":[2],"many":[3],"algorithms":[4],"are":[5],"designed":[6],"to":[7,24,27,31,39,67],"operate":[8],"on":[9,88],"grayscale":[10,28,40,85],"images.":[11],"This":[12,80],"is":[13,78],"because":[14],"of":[15],"speed,":[16],"memory":[17],"or":[18,49],"algorithm":[19],"restrictions.":[20],"Color":[21],"images":[22,38],"need":[23],"be":[25,42,68],"converted":[26],"in":[29,71,98],"order":[30],"apply":[32],"the":[33,47,50,56,72,84,93],"algorithms.":[34],"Converting":[35],"large":[36],"color":[37],"can":[41],"done":[43],"by":[44,55],"using":[45],"either":[46],"CPU":[48,94],"GPU.":[51],"Even":[52],"if":[53],"restricted":[54],"power":[57,66],"consumption,":[58],"mobile":[59,89],"GPUs":[60],"and":[61,91,95,101],"CPUs":[62],"have":[63],"enough":[64],"processing":[65,97],"viable":[69],"options":[70],"situation":[73],"where":[74],"no":[75],"desktop":[76],"equivalent":[77],"available.":[79],"paper":[81],"will":[82],"investigate":[83],"conversion":[87],"platforms,":[90],"compare":[92],"GPU":[96],"both":[99],"speeds":[100],"operation":[102],"complexity.":[103]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2775119854","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-04-08T03:56:24.721695","created_date":"2017-12-22"}