{"id":"https://openalex.org/W4410357449","doi":"https://doi.org/10.1145/3672608.3707994","title":"Student Research Abstract: Dynamic Adversarial Soil Modeling: A GAN-Confident Learning Approach for Precision Agriculture","display_name":"Student Research Abstract: Dynamic Adversarial Soil Modeling: A GAN-Confident Learning Approach for Precision Agriculture","publication_year":2025,"publication_date":"2025-03-31","ids":{"openalex":"https://openalex.org/W4410357449","doi":"https://doi.org/10.1145/3672608.3707994"},"language":"en","primary_location":{"id":"doi:10.1145/3672608.3707994","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3672608.3707994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing","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/A5082202439","display_name":"Vasu Jindal","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vasu Jindal","raw_affiliation_strings":["Columbia University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5082202439"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08367982,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1306","last_page":"1308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9950000047683716,"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":0.9950000047683716,"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/T12045","display_name":"Rice Cultivation and Yield Improvement","score":0.921999990940094,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9003999829292297,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8002393245697021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6245708465576172},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.6057384610176086},{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.47288718819618225},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.3969668745994568},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2526407241821289},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15418526530265808},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.06304505467414856}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8002393245697021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6245708465576172},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.6057384610176086},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.47288718819618225},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.3969668745994568},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2526407241821289},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15418526530265808},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.06304505467414856},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3672608.3707994","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3672608.3707994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2038782607","https://openalex.org/W2607747353","https://openalex.org/W2981116508","https://openalex.org/W3016616248","https://openalex.org/W3156669901","https://openalex.org/W3176680278","https://openalex.org/W4294636856","https://openalex.org/W4382318504"],"related_works":["https://openalex.org/W3201212491","https://openalex.org/W4380767732","https://openalex.org/W2382920002","https://openalex.org/W4247744717","https://openalex.org/W3161605631","https://openalex.org/W1551473783","https://openalex.org/W2912977869","https://openalex.org/W2170509036","https://openalex.org/W3195856620","https://openalex.org/W2622264455"],"abstract_inverted_index":{"Precision":[0],"agriculture":[1],"faces":[2],"significant":[3,118],"challenges":[4],"in":[5,120],"optimizing":[6],"water":[7,18,121],"usage":[8,122],"while":[9,123],"maintaining":[10],"crop":[11,125],"yields,":[12],"particularly":[13],"as":[14],"climate":[15],"change":[16],"intensifies":[17],"scarcity.":[19],"This":[20],"paper":[21],"introduces":[22],"Dynamic":[23],"Adversarial":[24,35],"Soil":[25],"Modeling":[26],"(DASM),":[27],"an":[28],"innovative":[29],"framework":[30],"that":[31],"synergistically":[32],"integrates":[33],"Generative":[34],"Networks":[36],"(GANs)":[37],"and":[38,77,80,100],"Confident":[39],"Learning":[40],"(CL)":[41],"for":[42,53,69,87,96],"precision":[43],"irrigation.":[44],"DASM's":[45],"novel":[46],"architecture":[47],"comprises:":[48],"(a)":[49],"a":[50,65,82,117],"conditional":[51],"GAN":[52],"synthetic":[54,78],"soil":[55,62,103],"state":[56,104],"generation,":[57],"capturing":[58],"complex":[59],"interdependencies":[60],"between":[61],"properties;":[63],"(b)":[64],"multi-class":[66],"CL":[67],"algorithm":[68],"robust":[70],"data":[71],"quality":[72],"assessment":[73],"of":[74],"both":[75],"sensor":[76],"data;":[79],"(c)":[81],"multi-task":[83],"learning":[84,95],"optimization":[85],"module":[86],"holistic":[88],"ecosystem":[89],"modeling.":[90],"The":[91],"system":[92],"employs":[93],"transfer":[94],"efficient":[97],"cross-domain":[98],"adaptation":[99],"outputs":[101],"probabilistic":[102],"distributions,":[105],"enabling":[106],"risk-aware":[107],"decision-making.":[108],"Compared":[109],"to":[110],"traditional":[111],"fixed-interval":[112],"irrigation":[113],"systems,":[114],"DASM":[115],"achieved":[116],"reduction":[119],"increasing":[124],"yields":[126],"by":[127],"12\u201316%.":[128]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}