{"id":"https://openalex.org/W2142336599","doi":"https://doi.org/10.1109/iccv.2009.5459187","title":"Higher-order gradient descent by fusion-move graph cut","display_name":"Higher-order gradient descent by fusion-move graph cut","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2142336599","doi":"https://doi.org/10.1109/iccv.2009.5459187","mag":"2142336599"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2009.5459187","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459187","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","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/A5061044862","display_name":"Hiroshi Ishikawa","orcid":"https://orcid.org/0000-0001-6310-5748"},"institutions":[{"id":"https://openalex.org/I33858575","display_name":"Nagoya City University","ror":"https://ror.org/04wn7wc95","country_code":"JP","type":"education","lineage":["https://openalex.org/I33858575"]},{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiroshi Ishikawa","raw_affiliation_strings":["Department of Information and Biological Sciences, University of Nagoya, Nagoya, Japan","[Nagoya City University, Department of Information and Biological Sciences, 1 Yamanohata Mizuho, 467-8501, Japan]"],"affiliations":[{"raw_affiliation_string":"Department of Information and Biological Sciences, University of Nagoya, Nagoya, Japan","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"[Nagoya City University, Department of Information and Biological Sciences, 1 Yamanohata Mizuho, 467-8501, Japan]","institution_ids":["https://openalex.org/I33858575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5061044862"],"corresponding_institution_ids":["https://openalex.org/I33858575","https://openalex.org/I60134161"],"apc_list":null,"apc_paid":null,"fwci":2.9121,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.92010762,"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":"568","last_page":"574"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9990000128746033,"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":0.9987000226974487,"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":0.5370691418647766},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4957321882247925},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4697924852371216},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45012521743774414},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4498528242111206},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.44198134541511536},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.433615118265152},{"id":"https://openalex.org/keywords/energy-minimization","display_name":"Energy minimization","score":0.41894111037254333},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.40278366208076477},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33462363481521606},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3278961181640625},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.301887571811676},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23069223761558533},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12615546584129333},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.09389179944992065},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09367963671684265}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5370691418647766},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4957321882247925},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4697924852371216},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45012521743774414},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4498528242111206},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.44198134541511536},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.433615118265152},{"id":"https://openalex.org/C14961307","wikidata":"https://www.wikidata.org/wiki/Q5377176","display_name":"Energy minimization","level":2,"score":0.41894111037254333},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40278366208076477},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33462363481521606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3278961181640625},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.301887571811676},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23069223761558533},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12615546584129333},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.09389179944992065},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09367963671684265},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"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/iccv.2009.5459187","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459187","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W38572207","https://openalex.org/W149871427","https://openalex.org/W1549521126","https://openalex.org/W2006293258","https://openalex.org/W2099835437","https://openalex.org/W2101309634","https://openalex.org/W2103498186","https://openalex.org/W2111559961","https://openalex.org/W2116064496","https://openalex.org/W2121845348","https://openalex.org/W2121927366","https://openalex.org/W2131686571","https://openalex.org/W2133374323","https://openalex.org/W2135165032","https://openalex.org/W2135968022","https://openalex.org/W2137117160","https://openalex.org/W2140502500","https://openalex.org/W2143516773","https://openalex.org/W2150734839","https://openalex.org/W2153396823","https://openalex.org/W2157394577","https://openalex.org/W2162366888","https://openalex.org/W2164918853","https://openalex.org/W2165949176","https://openalex.org/W2169066680","https://openalex.org/W2171675680","https://openalex.org/W6601516414","https://openalex.org/W6606103862","https://openalex.org/W6632941271","https://openalex.org/W6677988828"],"related_works":["https://openalex.org/W2029983961","https://openalex.org/W1576780264","https://openalex.org/W2358463731","https://openalex.org/W2548579603","https://openalex.org/W2107884096","https://openalex.org/W2352248461","https://openalex.org/W2140789035","https://openalex.org/W2170842100","https://openalex.org/W2000129726","https://openalex.org/W1563036098"],"abstract_inverted_index":{"Markov":[0],"Random":[1],"Field":[2],"is":[3,52,75],"now":[4],"ubiquitous":[5],"in":[6,122],"many":[7],"formulations":[8],"of":[9,15,26,35,59,84,95],"various":[10],"vision":[11],"problems.":[12],"Recently,":[13],"optimization":[14,61],"higher-order":[16,21,36,72,97],"potentials":[17],"became":[18],"practical":[19],"using":[20,120],"graph":[22,98],"cuts:":[23],"the":[24,28,33,44,48,55,60,67,93,96,111],"combination":[25],"i)":[27],"fusion":[29,49],"move":[30],"algorithm,":[31],"ii)":[32],"reduction":[34],"binary":[37],"energy":[38],"minimization":[39],"to":[40,62],"first-order,":[41],"and":[42,57,100,124],"iii)":[43],"QPBO":[45],"algorithm.":[46],"In":[47,87],"move,":[50],"it":[51,74],"crucial":[53],"for":[54,105],"success":[56],"efficiency":[58,94],"provide":[63],"proposals":[64],"that":[65,109],"fits":[66],"energies":[68],"being":[69],"optimized.":[70],"For":[71],"energies,":[73],"even":[76],"more":[77,114],"so":[78],"because":[79],"they":[80],"have":[81],"richer":[82],"class":[83],"null":[85],"potentials.":[86],"this":[88],"paper,":[89],"we":[90,117],"focus":[91],"on":[92],"cuts":[99],"present":[101],"a":[102],"simple":[103],"technique":[104],"generating":[106],"proposal":[107],"labelings":[108],"makes":[110],"algorithm":[112],"much":[113],"efficient,":[115],"which":[116],"empirically":[118],"show":[119],"examples":[121],"stereo":[123],"image":[125],"denoising.":[126]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
