{"id":"https://openalex.org/W2995128385","doi":"https://doi.org/10.1109/tencon.2019.8929334","title":"Obstacle Detection, Depth Estimation And Warning System For Visually Impaired People","display_name":"Obstacle Detection, Depth Estimation And Warning System For Visually Impaired People","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2995128385","doi":"https://doi.org/10.1109/tencon.2019.8929334","mag":"2995128385"},"language":"en","primary_location":{"id":"doi:10.1109/tencon.2019.8929334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2019.8929334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON)","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/A5108778176","display_name":"K C Shahira","orcid":null},"institutions":[{"id":"https://openalex.org/I114845381","display_name":"National Institute of Technology Calicut","ror":"https://ror.org/03yyd7552","country_code":"IN","type":"education","lineage":["https://openalex.org/I114845381"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"K C Shahira","raw_affiliation_strings":["Computer Science and Engineering, NIT Calicut, India"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, NIT Calicut, India","institution_ids":["https://openalex.org/I114845381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010334971","display_name":"Sagar Tripathy","orcid":null},"institutions":[{"id":"https://openalex.org/I114845381","display_name":"National Institute of Technology Calicut","ror":"https://ror.org/03yyd7552","country_code":"IN","type":"education","lineage":["https://openalex.org/I114845381"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sagar Tripathy","raw_affiliation_strings":["Computer Science and Engineering, NIT Calicut, India"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, NIT Calicut, India","institution_ids":["https://openalex.org/I114845381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010786471","display_name":"A Lijiya","orcid":null},"institutions":[{"id":"https://openalex.org/I114845381","display_name":"National Institute of Technology Calicut","ror":"https://ror.org/03yyd7552","country_code":"IN","type":"education","lineage":["https://openalex.org/I114845381"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A Lijiya","raw_affiliation_strings":["Computer Science and Engineering, NIT Calicut, India"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, NIT Calicut, India","institution_ids":["https://openalex.org/I114845381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5108778176"],"corresponding_institution_ids":["https://openalex.org/I114845381"],"apc_list":null,"apc_paid":null,"fwci":0.9729,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.74792848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"863","last_page":"868"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9987999796867371,"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/obstacle","display_name":"Obstacle","score":0.817981481552124},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7898409366607666},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7031600475311279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6742995381355286},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5845389366149902},{"id":"https://openalex.org/keywords/mobile-phone","display_name":"Mobile phone","score":0.500514030456543},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4902270436286926},{"id":"https://openalex.org/keywords/ultrasonic-sensor","display_name":"Ultrasonic sensor","score":0.44028687477111816},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43518805503845215},{"id":"https://openalex.org/keywords/warning-system","display_name":"Warning system","score":0.43209874629974365},{"id":"https://openalex.org/keywords/phone","display_name":"Phone","score":0.4102451205253601},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.35148128867149353},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.19601774215698242},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12186229228973389},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.09469902515411377},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.0936734676361084}],"concepts":[{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.817981481552124},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7898409366607666},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7031600475311279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6742995381355286},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5845389366149902},{"id":"https://openalex.org/C2777421447","wikidata":"https://www.wikidata.org/wiki/Q17517","display_name":"Mobile phone","level":2,"score":0.500514030456543},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4902270436286926},{"id":"https://openalex.org/C81288441","wikidata":"https://www.wikidata.org/wiki/Q20736125","display_name":"Ultrasonic sensor","level":2,"score":0.44028687477111816},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43518805503845215},{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.43209874629974365},{"id":"https://openalex.org/C2778707766","wikidata":"https://www.wikidata.org/wiki/Q202064","display_name":"Phone","level":2,"score":0.4102451205253601},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.35148128867149353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.19601774215698242},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12186229228973389},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.09469902515411377},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0936734676361084},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon.2019.8929334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2019.8929334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2123436043","https://openalex.org/W2129793894","https://openalex.org/W2163605009","https://openalex.org/W2253806798","https://openalex.org/W2527888204","https://openalex.org/W2587718917","https://openalex.org/W2595958025","https://openalex.org/W2618530766","https://openalex.org/W2753027569","https://openalex.org/W2769986739","https://openalex.org/W2784083162","https://openalex.org/W2787284273","https://openalex.org/W2798131626","https://openalex.org/W2963037989","https://openalex.org/W2963658615","https://openalex.org/W3097096317","https://openalex.org/W4293584584","https://openalex.org/W4295246343"],"related_works":["https://openalex.org/W2794103424","https://openalex.org/W1996530509","https://openalex.org/W3028317537","https://openalex.org/W2389515972","https://openalex.org/W4245435724","https://openalex.org/W2055301889","https://openalex.org/W4400979532","https://openalex.org/W2376554934","https://openalex.org/W2077790809","https://openalex.org/W1505959757"],"abstract_inverted_index":{"The":[0,48,60,93,127],"work":[1,113],"aims":[2],"to":[3,30,110],"develop":[4],"a":[5,115],"system":[6,49,86,94,129],"which":[7],"assists":[8],"the":[9,23,32,46,53,67,85,97,100,125,147],"blind":[10],"people":[11],"in":[12],"sensing":[13],"and":[14],"identifying":[15],"obstacles":[16],"on":[17,79],"their":[18],"way.":[19],"It":[20],"also":[21],"estimates":[22],"distance":[24,44],"towards":[25],"them.":[26],"We":[27,83,108],"use":[28],"Yolov2":[29],"train":[31],"system.":[33],"With":[34],"this,":[35],"an":[36,56,75,80,150],"image":[37],"description":[38],"is":[39,63],"produced":[40],"along":[41,135],"with":[42,55,72,105,136,139],"its":[43],"from":[45],"person.":[47],"would":[50],"then":[51],"present":[52],"person":[54],"appropriate":[57],"audio":[58],"response.":[59],"range":[61],"information":[62],"obtained":[64],"by":[65,121],"merging":[66],"output":[68],"of":[69,74,124,149],"object":[70,98,133],"detector":[71],"that":[73],"ultrasonic":[76],"sensor":[77],"mounted":[78],"Auridino":[81],"Uno.":[82],"evaluated":[84],"both":[87],"indoors":[88],"as":[89,91],"well":[90],"outdoors.":[92],"can":[95,130,144],"detect":[96],"using":[99],"pre-trained":[101],"deep":[102],"neural":[103],"network":[104],"97%":[106],"accuracy.":[107],"want":[109],"extend":[111],"this":[112],"into":[114],"portable":[116],"device":[117],"like":[118],"mobile":[119],"phone":[120],"transfer":[122],"learning":[123],"model.":[126],"proposed":[128],"identify":[131,145],"more":[132],"categories":[134],"depth":[137],"estimation,":[138],"reasonable":[140],"accuracy,":[141],"while":[142],"others":[143],"only":[146],"presence":[148],"obstacle.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
