{"id":"https://openalex.org/W4411624643","doi":"https://doi.org/10.1145/3703323.3704272","title":"Automatic Generation of Highly Accurate Parameter-optimal Segmentation Models in Precision Agriculture","display_name":"Automatic Generation of Highly Accurate Parameter-optimal Segmentation Models in Precision Agriculture","publication_year":2024,"publication_date":"2024-12-18","ids":{"openalex":"https://openalex.org/W4411624643","doi":"https://doi.org/10.1145/3703323.3704272"},"language":"en","primary_location":{"id":"doi:10.1145/3703323.3704272","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703323.3704272","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3703323.3704272","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3703323.3704272","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Swarnava Dey","orcid":"https://orcid.org/0000-0002-3988-1445"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Swarnava Dey","raw_affiliation_strings":["TCS Research, Tata Consultancy Services Ltd., Kolkata, West Bengal, India"],"affiliations":[{"raw_affiliation_string":"TCS Research, Tata Consultancy Services Ltd., Kolkata, West Bengal, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111178555","display_name":"Soma Dasgupta","orcid":"https://orcid.org/0009-0006-6272-7661"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Soma Dasgupta","raw_affiliation_strings":["Tata Consultancy Services Limited, Kolkata, West Bengal, India"],"affiliations":[{"raw_affiliation_string":"Tata Consultancy Services Limited, Kolkata, West Bengal, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16676599,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"395","last_page":"399"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12486","display_name":"Food Supply Chain Traceability","score":0.9524999856948853,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11978","display_name":"Soil Mechanics and Vehicle Dynamics","score":0.948199987411499,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.625230073928833},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6188638806343079},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5523918867111206},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4964178204536438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48621121048927307},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42763108015060425},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3515884280204773},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.25770798325538635},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05998608469963074}],"concepts":[{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.625230073928833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6188638806343079},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5523918867111206},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4964178204536438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48621121048927307},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42763108015060425},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3515884280204773},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.25770798325538635},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05998608469963074},{"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:10.1145/3703323.3704272","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703323.3704272","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3703323.3704272","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3703323.3704272","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703323.3704272","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3703323.3704272","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411624643.pdf","grobid_xml":"https://content.openalex.org/works/W4411624643.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2185841109","https://openalex.org/W2751390451","https://openalex.org/W2755766995","https://openalex.org/W2808938483","https://openalex.org/W2962953743","https://openalex.org/W2963323244","https://openalex.org/W2971480543","https://openalex.org/W2990265654","https://openalex.org/W3015774841","https://openalex.org/W3120697286","https://openalex.org/W3132104078","https://openalex.org/W3160945783","https://openalex.org/W4316096722","https://openalex.org/W4319300810","https://openalex.org/W4379046973","https://openalex.org/W4380928218","https://openalex.org/W4381747112","https://openalex.org/W4385577621","https://openalex.org/W4388502411","https://openalex.org/W4390874575","https://openalex.org/W4391285291","https://openalex.org/W4395028770","https://openalex.org/W4395054533","https://openalex.org/W4399324395"],"related_works":["https://openalex.org/W2381688409","https://openalex.org/W2097971044","https://openalex.org/W1895773911","https://openalex.org/W4367055784","https://openalex.org/W4251198372","https://openalex.org/W4379231730","https://openalex.org/W2162001954","https://openalex.org/W2376314062","https://openalex.org/W4389858081","https://openalex.org/W1522196789"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"demonstrate":[4],"how":[5],"an":[6],"existing":[7],"AutoML":[8,28,79],"tool":[9],"can":[10,72],"be":[11,73],"enhanced":[12],"to":[13],"generate":[14],"highly":[15],"accurate":[16,49],"yet":[17,50],"edge-friendly":[18],"segmentation":[19,43,52],"models":[20,35,53,71],"for":[21,36],"precision":[22,58],"agriculture.":[23],"Currently,":[24],"only":[25,77],"a":[26],"few":[27],"tools":[29],"are":[30],"capable":[31],"of":[32,89],"producing":[33],"TinyML":[34],"dense":[37],"computer":[38],"vision":[39],"tasks,":[40],"such":[41,61,70],"as":[42,62],"and":[44,64,82],"object":[45],"detection.":[46],"Furthermore,":[47],"creating":[48],"parameter-efficient":[51],"is":[54,93],"particularly":[55],"challenging":[56],"in":[57],"agriculture":[59],"applications,":[60],"crop":[63],"weed":[65],"segmentation.":[66],"We":[67],"show":[68],"that":[69],"achieved":[74],"by":[75],"invoking":[76],"two":[78],"API":[80],"functions":[81],"tuning":[83,91],"just":[84],"four":[85],"hyperparameters.":[86],"A":[87],"video":[88],"the":[90],"process":[92],"available":[94],"at:":[95],"https://youtu.be/L3MyXkVTzCc.":[96]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
