{"id":"https://openalex.org/W3091279095","doi":"https://doi.org/10.1109/icra40945.2020.9196614","title":"Reinforcement Learning for Adaptive Illumination with X-rays","display_name":"Reinforcement Learning for Adaptive Illumination with X-rays","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3091279095","doi":"https://doi.org/10.1109/icra40945.2020.9196614","mag":"3091279095"},"language":"en","primary_location":{"id":"doi:10.1109/icra40945.2020.9196614","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9196614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","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/A5091188638","display_name":"Jean-Raymond Betterton","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jean-Raymond Betterton","raw_affiliation_strings":["Department of Computer Science, Stanford University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047648085","display_name":"Daniel Ratner","orcid":"https://orcid.org/0000-0002-5747-7323"},"institutions":[{"id":"https://openalex.org/I2801935854","display_name":"SLAC National Accelerator Laboratory","ror":"https://ror.org/05gzmn429","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I2801935854","https://openalex.org/I39565521","https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Ratner","raw_affiliation_strings":["SLAC National Accelerator Laboratory"],"affiliations":[{"raw_affiliation_string":"SLAC National Accelerator Laboratory","institution_ids":["https://openalex.org/I2801935854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060067287","display_name":"Samuel M. Webb","orcid":"https://orcid.org/0000-0003-1188-0464"},"institutions":[{"id":"https://openalex.org/I2801935854","display_name":"SLAC National Accelerator Laboratory","ror":"https://ror.org/05gzmn429","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I2801935854","https://openalex.org/I39565521","https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samuel Webb","raw_affiliation_strings":["SLAC National Accelerator Laboratory"],"affiliations":[{"raw_affiliation_string":"SLAC National Accelerator Laboratory","institution_ids":["https://openalex.org/I2801935854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068326377","display_name":"Mykel J. Kochenderfer","orcid":"https://orcid.org/0000-0002-7238-9663"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mykel Kochenderfer","raw_affiliation_strings":["Department of Computer Science, Stanford University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Stanford University","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091188638"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":0.7954,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.78663831,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"328","last_page":"334"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.995199978351593,"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"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.995199978351593,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9948999881744385,"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":0.9922000169754028,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.838481605052948},{"id":"https://openalex.org/keywords/scanner","display_name":"Scanner","score":0.6911226511001587},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6667371392250061},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6386772394180298},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6292172074317932},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6286563277244568},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5856420993804932},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5662738680839539},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5152950286865234},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4885624349117279},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4608208239078522},{"id":"https://openalex.org/keywords/data-acquisition","display_name":"Data acquisition","score":0.429551362991333}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.838481605052948},{"id":"https://openalex.org/C2779751349","wikidata":"https://www.wikidata.org/wiki/Q1474480","display_name":"Scanner","level":2,"score":0.6911226511001587},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6667371392250061},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6386772394180298},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6292172074317932},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6286563277244568},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5856420993804932},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5662738680839539},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5152950286865234},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4885624349117279},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4608208239078522},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.429551362991333},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra40945.2020.9196614","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9196614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1640287697","https://openalex.org/W1967917063","https://openalex.org/W1968270353","https://openalex.org/W1969288121","https://openalex.org/W1976003562","https://openalex.org/W1992692106","https://openalex.org/W2026871222","https://openalex.org/W2051434435","https://openalex.org/W2053849251","https://openalex.org/W2071899498","https://openalex.org/W2101926813","https://openalex.org/W2119667497","https://openalex.org/W2125069195","https://openalex.org/W2128659236","https://openalex.org/W2145096794","https://openalex.org/W2147800946","https://openalex.org/W2151131483","https://openalex.org/W2151965738","https://openalex.org/W2161674001","https://openalex.org/W2514699275","https://openalex.org/W2557540810","https://openalex.org/W2563408008","https://openalex.org/W2596367596","https://openalex.org/W2767161633","https://openalex.org/W2800178118","https://openalex.org/W2883247834","https://openalex.org/W2885092869","https://openalex.org/W2897317924","https://openalex.org/W2903158431","https://openalex.org/W2907340087","https://openalex.org/W2949071206","https://openalex.org/W2951025196","https://openalex.org/W2963696295","https://openalex.org/W2967096001","https://openalex.org/W2968418511","https://openalex.org/W3007384386","https://openalex.org/W4214717370","https://openalex.org/W4250955649","https://openalex.org/W4294526978","https://openalex.org/W6682262322","https://openalex.org/W6733556328","https://openalex.org/W6735641298","https://openalex.org/W6741776117","https://openalex.org/W6756615331","https://openalex.org/W6757797063"],"related_works":["https://openalex.org/W4232857084","https://openalex.org/W4245233074","https://openalex.org/W2167384162","https://openalex.org/W2001485867","https://openalex.org/W4402492658","https://openalex.org/W1517555227","https://openalex.org/W2653993779","https://openalex.org/W2911295078","https://openalex.org/W762151464","https://openalex.org/W2389610024"],"abstract_inverted_index":{"We":[0,12,30,41,85,106],"propose":[1],"a":[2,21,48,55,97,111],"learning":[3,50],"algorithm":[4],"for":[5,74,110],"automating":[6],"image":[7,28],"sampling":[8],"in":[9],"scientific":[10],"applications.":[11],"consider":[13],"settings":[14],"where":[15],"images":[16,35],"are":[17],"sampled":[18],"by":[19,36],"controlling":[20],"probe":[22],"beam's":[23],"scanning":[24],"trajectory":[25],"over":[26],"the":[27,37,43,61,66,69,94],"surface.":[29],"explore":[31],"alternatives":[32],"to":[33,57,92,99,103],"obtaining":[34],"standard":[38],"rastering":[39],"method.":[40],"formulate":[42],"scanner":[44,95],"control":[45,93],"problem":[46,52],"as":[47,96],"reinforcement":[49],"(RL)":[51],"and":[53,72,118],"train":[54],"policy":[56,113],"adaptively":[58],"sample":[59,76],"only":[60],"highest":[62],"value":[63],"regions":[64],"of":[65,82],"image,":[67],"choosing":[68],"acquisition":[70],"time":[71],"resolution":[73],"each":[75],"position":[77],"based":[78],"on":[79,114],"an":[80,123],"observation":[81],"previous":[83],"readings.":[84],"use":[86],"convolutional":[87],"neural":[88],"network":[89],"(CNN)":[90],"policies":[91],"way":[98],"generalize":[100],"our":[101],"approach":[102],"larger":[104],"samples.":[105],"show":[107],"simulation":[108],"results":[109],"simple":[112],"both":[115],"synthetic":[116],"data":[117,121],"real":[119],"world":[120],"from":[122],"archaeological":[124],"application.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}