{"id":"https://openalex.org/W2791234994","doi":"https://doi.org/10.1109/icra.2018.8461089","title":"DPDB-Net: Exploiting Dense Connections for Convolutional Encoders","display_name":"DPDB-Net: Exploiting Dense Connections for Convolutional Encoders","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2791234994","doi":"https://doi.org/10.1109/icra.2018.8461089","mag":"2791234994"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2018.8461089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2018.8461089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 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/A5034236726","display_name":"Gabriel L. Oliveira","orcid":"https://orcid.org/0000-0003-0099-9873"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Gabriel L. Oliveira","raw_affiliation_strings":["Department of Computer Science at the University of Freiburg, Freiburg, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science at the University of Freiburg, Freiburg, Germany","institution_ids":["https://openalex.org/I161046081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084499878","display_name":"Wolfram Burgard","orcid":"https://orcid.org/0000-0002-5680-6500"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfram Burgard","raw_affiliation_strings":["Department of Computer Science at the University of Freiburg, Freiburg, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science at the University of Freiburg, Freiburg, Germany","institution_ids":["https://openalex.org/I161046081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070290355","display_name":"Thomas Brox","orcid":"https://orcid.org/0000-0002-6282-8861"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Brox","raw_affiliation_strings":["Department of Computer Science at the University of Freiburg, Freiburg, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science at the University of Freiburg, Freiburg, Germany","institution_ids":["https://openalex.org/I161046081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034236726"],"corresponding_institution_ids":["https://openalex.org/I161046081"],"apc_list":null,"apc_paid":null,"fwci":0.3257,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65476879,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"41","issue":null,"first_page":"4525","last_page":"4531"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9983000159263611,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9983000159263611,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.996999979019165,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8325504064559937},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7467669248580933},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7293463945388794},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6756970882415771},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5816630125045776},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4741230309009552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4675504267215729},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.459870308637619},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4213525652885437},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3845047056674957},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15604734420776367}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8325504064559937},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7467669248580933},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7293463945388794},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6756970882415771},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5816630125045776},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4741230309009552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4675504267215729},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.459870308637619},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4213525652885437},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3845047056674957},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15604734420776367},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra.2018.8461089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2018.8461089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:freidok.uni-freiburg.de:144617","is_oa":false,"landing_page_url":"https://freidok.uni-freiburg.de/data/144617","pdf_url":null,"source":{"id":"https://openalex.org/S4306401057","display_name":"FreiDok plus (Universit\u00e4tsbibliothek Freiburg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I161046081","host_organization_name":"University of Freiburg","host_organization_lineage":["https://openalex.org/I161046081"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2018 IEEE International Conference on Robotics and Automation (ICRA). , 2018., ISBN: 9781538630815","raw_type":"article_in_conference_proceedings"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W360623563","https://openalex.org/W1162411702","https://openalex.org/W1542723449","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W1938976761","https://openalex.org/W1961270558","https://openalex.org/W2108598243","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2254462240","https://openalex.org/W2264432461","https://openalex.org/W2290577462","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2535516436","https://openalex.org/W2598666589","https://openalex.org/W2600777408","https://openalex.org/W2623430965","https://openalex.org/W2963166928","https://openalex.org/W2963285578","https://openalex.org/W2963446712","https://openalex.org/W4239072543"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W4293226380","https://openalex.org/W2788972299","https://openalex.org/W4390516098","https://openalex.org/W2521347458","https://openalex.org/W2498789492","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2729981612"],"abstract_inverted_index":{"Densely":[0],"connected":[1],"networks":[2,21],"for":[3,38],"classification":[4,15],"enable":[5],"feature":[6,28,55,59,68,78],"exploration":[7,60],"and":[8,57,104,113],"result":[9],"in":[10,61,81,89,100],"state-of-the-art":[11,106],"performance":[12,107],"on":[13,108,116],"multiple":[14,101],"tasks.":[16],"The":[17],"alternative":[18],"to":[19,76],"dense":[20,51],"is":[22,86],"the":[23,62,71,82,93,109,117],"residual":[24,72],"network":[25,73],"which":[26,41,53],"enables":[27],"re-usage.":[29],"In":[30],"this":[31,90],"work,":[32],"we":[33,42,65],"combine":[34],"these":[35],"orthogonal":[36],"concepts":[37],"encoder-decoder":[39],"architectures,":[40],"call":[43],"Dual-Path":[44],"Dense-Block":[45],"Network":[46],"(DPDB-Net).":[47],"We":[48,95],"introduce":[49],"a":[50,77],"block":[52],"incorporates":[54],"re-usage":[56,69],"new":[58],"encoder.":[63],"Moreover,":[64],"discuss":[66],"that":[67],"by":[70],"architecture":[74,99],"leads":[75],"map":[79],"explosion":[80],"decoder":[83],"and,":[84],"thus,":[85],"not":[87],"advantageous":[88],"part":[91],"of":[92],"network.":[94],"evaluated":[96],"our":[97],"proposed":[98],"segmentation":[102],"tasks":[103],"report":[105],"Freiburg":[110],"Forest":[111],"dataset":[112],"competitive":[114],"results":[115],"Cam":[118],"Vid":[119],"dataset.":[120]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}