{"id":"https://openalex.org/W3135474317","doi":"https://doi.org/10.1109/dicta51227.2020.9363428","title":"W-A net: Leveraging Atrous and Deformable Convolutions for Efficient Text Detection","display_name":"W-A net: Leveraging Atrous and Deformable Convolutions for Efficient Text Detection","publication_year":2020,"publication_date":"2020-11-29","ids":{"openalex":"https://openalex.org/W3135474317","doi":"https://doi.org/10.1109/dicta51227.2020.9363428","mag":"3135474317"},"language":"en","primary_location":{"id":"doi:10.1109/dicta51227.2020.9363428","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta51227.2020.9363428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 Digital Image Computing: Techniques and Applications (DICTA)","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/A5013455807","display_name":"Sukhad Anand","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sukhad Anand","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5040210218","display_name":"Zoya Khan","orcid":"https://orcid.org/0009-0006-6680-4281"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zoya Khan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013455807"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18479868,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"233","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":1.0,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":1.0,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9851999878883362,"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/text-detection","display_name":"Text detection","score":0.796858549118042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7439399361610413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7112581729888916},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6736807823181152},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5565565824508667},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5396144390106201},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5374871492385864},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.5010440349578857},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4695984125137329},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4574306607246399},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45166707038879395},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4169774651527405},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41670626401901245},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32263436913490295},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15043726563453674}],"concepts":[{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.796858549118042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7439399361610413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7112581729888916},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6736807823181152},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5565565824508667},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5396144390106201},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5374871492385864},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.5010440349578857},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4695984125137329},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4574306607246399},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45166707038879395},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4169774651527405},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41670626401901245},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32263436913490295},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15043726563453674},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/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/dicta51227.2020.9363428","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta51227.2020.9363428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W603908379","https://openalex.org/W1491389626","https://openalex.org/W1901129140","https://openalex.org/W2074849287","https://openalex.org/W2116627672","https://openalex.org/W2144554289","https://openalex.org/W2157317150","https://openalex.org/W2194775991","https://openalex.org/W2431743448","https://openalex.org/W2519818067","https://openalex.org/W2550687635","https://openalex.org/W2559800592","https://openalex.org/W2589788440","https://openalex.org/W2601564443","https://openalex.org/W2604735854","https://openalex.org/W2605076167","https://openalex.org/W2605982830","https://openalex.org/W2683784395","https://openalex.org/W2772800855","https://openalex.org/W2791835744","https://openalex.org/W2806581075","https://openalex.org/W2810028092","https://openalex.org/W2810983211","https://openalex.org/W2831607544","https://openalex.org/W2886307529","https://openalex.org/W2891117443","https://openalex.org/W2899996070","https://openalex.org/W2935408319","https://openalex.org/W2949846184","https://openalex.org/W2962810613","https://openalex.org/W2963647456","https://openalex.org/W2963836589","https://openalex.org/W2966926453","https://openalex.org/W2967591398","https://openalex.org/W2971022097","https://openalex.org/W2987696791","https://openalex.org/W2998621280","https://openalex.org/W3015404287","https://openalex.org/W3035449864","https://openalex.org/W3091091787","https://openalex.org/W3093218477","https://openalex.org/W3161196401","https://openalex.org/W4288021837","https://openalex.org/W6618372016","https://openalex.org/W6629590909","https://openalex.org/W6639824700","https://openalex.org/W6729983426","https://openalex.org/W6733171302","https://openalex.org/W6739684510","https://openalex.org/W6746284755","https://openalex.org/W6747438827","https://openalex.org/W6752159816","https://openalex.org/W6752534923","https://openalex.org/W6754160228","https://openalex.org/W6755730432","https://openalex.org/W6761480002","https://openalex.org/W6768159128","https://openalex.org/W6770133954","https://openalex.org/W6770629681"],"related_works":["https://openalex.org/W1522196789","https://openalex.org/W2978383222","https://openalex.org/W2172629291","https://openalex.org/W2380773642","https://openalex.org/W2384559435","https://openalex.org/W2337707338","https://openalex.org/W2393940967","https://openalex.org/W2058548953","https://openalex.org/W2785359773","https://openalex.org/W2385598138"],"abstract_inverted_index":{"Scene":[0],"text":[1,21,55,60,139,156,169,186,194],"detection":[2,140,187],"has":[3],"been":[4],"gaining":[5],"a":[6,29,64,88,103,143,172],"lots":[7],"of":[8,38,73,147,154],"focus":[9],"in":[10,22,53,58,134,157],"research.":[11],"Even":[12],"though":[13],"the":[14,78,93,125,148],"recent":[15,184],"methods":[16,188],"are":[17],"able":[18],"to":[19,108,123,130],"detect":[20,131],"complex":[23,26],"background":[24],"having":[25],"shapes":[27],"with":[28,77,199],"fairly":[30],"good":[31],"accuracy,":[32],"they":[33],"still":[34],"suffer":[35],"from":[36,44,112],"issues":[37],"limited":[39],"receptive":[40,126],"field.":[41],"These":[42],"fail":[43],"detecting":[45,54,155],"extremely":[46],"short":[47,200],"or":[48,159],"long":[49,132],"words":[50,56,111,133],"hence":[51],"failing":[52],"precisely":[57],"document":[59,160,193],"images.":[61,161],"We":[62,115,137,162],"propose":[63],"new":[65],"model":[66,86,152],"which":[67,91,106,128,189],"we":[68],"call":[69],"W-A":[70],"net,":[71],"because":[72],"it's":[74],"W":[75],"shape":[76],"middle":[79],"branch":[80],"being":[81],"Atrous":[82,117],"convolutional":[83,121],"layers.":[84],"Our":[85,175],"predicts":[87],"segmentation":[89],"map":[90,105],"divides":[92],"image":[94],"into":[95],"word":[96,99],"and":[97,101,119,171],"no":[98],"regions":[100],"also,":[102],"boundary":[104],"helps":[107,129],"segregate":[109],"closer":[110],"each":[113],"other.":[114],"use":[116],"convolutions":[118],"Deformable":[120],"layers":[122],"increase":[124],"field":[127],"an":[135],"image.":[136],"treat":[138],"problem":[141,145],"as":[142],"single":[144],"irrespective":[146],"background,":[149],"making":[150],"our":[151,164,179],"suitable":[153],"scene":[158,168,185],"present":[163],"findings":[165],"on":[166,192],"two":[167],"datasets":[170],"receipt":[173,197],"dataset.":[174],"results":[176],"show":[177],"that":[178],"method":[180],"performs":[181],"better":[182],"than":[183],"perform":[190],"poorly":[191],"images,":[195],"especially":[196],"images":[198],"words.":[201]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
