{"id":"https://openalex.org/W2758789045","doi":"https://doi.org/10.1109/mlsp.2017.8168137","title":"Navigation-Based learning for survey trajectory classification in autonomous underwater vehicles","display_name":"Navigation-Based learning for survey trajectory classification in autonomous underwater vehicles","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2758789045","doi":"https://doi.org/10.1109/mlsp.2017.8168137","mag":"2758789045"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2017.8168137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2017.8168137","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5042862102","display_name":"Mariela De Lucas \u00c1lvarez","orcid":"https://orcid.org/0000-0003-0846-4507"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"M. De Lucas Alvarez","raw_affiliation_strings":["Ocean Systems Laboratory, Heriot-Watt University, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"Ocean Systems Laboratory, Heriot-Watt University, Edinburgh, UK","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084819987","display_name":"Helen Hastie","orcid":"https://orcid.org/0000-0002-9177-7282"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"H. Hastie","raw_affiliation_strings":["School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113592636","display_name":"David M. Lane","orcid":null},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"D. Lane","raw_affiliation_strings":["Ocean Systems Laboratory, Heriot-Watt University, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"Ocean Systems Laboratory, Heriot-Watt University, Edinburgh, UK","institution_ids":["https://openalex.org/I32062511"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042862102"],"corresponding_institution_ids":["https://openalex.org/I32062511"],"apc_list":null,"apc_paid":null,"fwci":0.8471,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75325016,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9891999959945679,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/trajectory","display_name":"Trajectory","score":0.8181356191635132},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7567445039749146},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6510375142097473},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6149141788482666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5826997756958008},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5528619885444641},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.4909222722053528},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.4765610992908478},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47577419877052307},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.465878427028656},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4569109380245209}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8181356191635132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7567445039749146},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6510375142097473},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6149141788482666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5826997756958008},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5528619885444641},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.4909222722053528},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.4765610992908478},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47577419877052307},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.465878427028656},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4569109380245209},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/mlsp.2017.8168137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2017.8168137","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G1255880519","display_name":null,"funder_award_id":"EP/J015040/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G646377064","display_name":null,"funder_award_id":"EP/J012432/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W142002057","https://openalex.org/W170770739","https://openalex.org/W592244745","https://openalex.org/W1504585805","https://openalex.org/W1506806321","https://openalex.org/W1554663460","https://openalex.org/W1678119466","https://openalex.org/W1904365287","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2102128709","https://openalex.org/W2110707662","https://openalex.org/W2113459411","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2135677455","https://openalex.org/W2141173017","https://openalex.org/W2144499799","https://openalex.org/W2155114033","https://openalex.org/W2170240176","https://openalex.org/W2435507717","https://openalex.org/W2524365899","https://openalex.org/W2597261100","https://openalex.org/W2747743240","https://openalex.org/W2949991226","https://openalex.org/W2963012544","https://openalex.org/W2963078493","https://openalex.org/W2964308564","https://openalex.org/W4388297464","https://openalex.org/W6605775231","https://openalex.org/W6617744952","https://openalex.org/W6640036494","https://openalex.org/W6674330103","https://openalex.org/W6676984168","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6685053522","https://openalex.org/W6734915346"],"related_works":["https://openalex.org/W4385280324","https://openalex.org/W2912153778","https://openalex.org/W4387163678","https://openalex.org/W4288108708","https://openalex.org/W2973430807","https://openalex.org/W2984436043","https://openalex.org/W2912831041","https://openalex.org/W2890685186","https://openalex.org/W2796130100","https://openalex.org/W3173606726"],"abstract_inverted_index":{"Timeseries":[0],"sensor":[1],"data":[2,52],"processing":[3],"is":[4],"indispensable":[5],"for":[6],"system":[7],"monitoring.":[8],"Working":[9],"with":[10],"autonomous":[11],"vehicles":[12],"requires":[13],"mechanisms":[14],"that":[15,71],"provide":[16],"insightful":[17],"information":[18],"about":[19],"the":[20,73,93],"status":[21],"of":[22,86,95],"a":[23,26,37],"mission.":[24],"In":[25,46],"setting":[27],"where":[28],"time":[29],"and":[30,43,57],"resources":[31],"are":[32],"limited,":[33],"trajectory":[34,55,78],"classification":[35],"plays":[36],"vital":[38],"role":[39],"in":[40],"mission":[41],"monitoring":[42],"failure":[44],"detection.":[45],"this":[47],"context,":[48],"we":[49],"use":[50],"navigational":[51],"to":[53],"interpret":[54],"patterns":[56,79],"classify":[58],"them.":[59],"We":[60,91],"implement":[61],"Long":[62],"Short-Term":[63],"Memory":[64],"(LSTM)":[65],"based":[66],"Recursive":[67],"Neural":[68],"Networks":[69],"(RNN)":[70],"learn":[72],"most":[74],"commonly":[75],"used":[76],"survey":[77],"from":[80],"surveys":[81],"executed":[82],"by":[83],"two":[84],"types":[85],"Autonomous":[87],"Underwater":[88],"Vehicles":[89],"(AUV).":[90],"compare":[92],"performance":[94],"our":[96],"network":[97],"against":[98],"baseline":[99],"machine":[100],"learning":[101],"methods.":[102]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}