{"id":"https://openalex.org/W4415723780","doi":"https://doi.org/10.1007/978-3-032-03705-3_4","title":"One Channel is All You Need: Optimizing Hyperspectral Data for\u00a0Crop Disease Detection","display_name":"One Channel is All You Need: Optimizing Hyperspectral Data for\u00a0Crop Disease Detection","publication_year":2025,"publication_date":"2025-10-31","ids":{"openalex":"https://openalex.org/W4415723780","doi":"https://doi.org/10.1007/978-3-032-03705-3_4"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-032-03705-3_4","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-032-03705-3_4","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5037252948","display_name":"Johan Buitenhuis","orcid":"https://orcid.org/0000-0001-8849-2596"},"institutions":[{"id":"https://openalex.org/I24027795","display_name":"University of Johannesburg","ror":"https://ror.org/04z6c2n17","country_code":"ZA","type":"education","lineage":["https://openalex.org/I24027795"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"John Albert Buitenhuis","raw_affiliation_strings":["Academy of Computer Science and Software Engineering, University of Johannesburg, Cnr University Road and Kingsway Avenue, Auckland Park, Johannesburg, 2092, Gauteng, South Africa"],"affiliations":[{"raw_affiliation_string":"Academy of Computer Science and Software Engineering, University of Johannesburg, Cnr University Road and Kingsway Avenue, Auckland Park, Johannesburg, 2092, Gauteng, South Africa","institution_ids":["https://openalex.org/I24027795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081793269","display_name":"Hima Vadapalli","orcid":"https://orcid.org/0000-0001-9040-3601"},"institutions":[{"id":"https://openalex.org/I24027795","display_name":"University of Johannesburg","ror":"https://ror.org/04z6c2n17","country_code":"ZA","type":"education","lineage":["https://openalex.org/I24027795"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Hima Vadapalli","raw_affiliation_strings":["Academy of Computer Science and Software Engineering, University of Johannesburg, Cnr University Road and Kingsway Avenue, Auckland Park, Johannesburg, 2092, Gauteng, South Africa"],"affiliations":[{"raw_affiliation_string":"Academy of Computer Science and Software Engineering, University of Johannesburg, Cnr University Road and Kingsway Avenue, Auckland Park, Johannesburg, 2092, Gauteng, South Africa","institution_ids":["https://openalex.org/I24027795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068464834","display_name":"Dustin van der Haar","orcid":"https://orcid.org/0000-0002-5632-1220"},"institutions":[{"id":"https://openalex.org/I24027795","display_name":"University of Johannesburg","ror":"https://ror.org/04z6c2n17","country_code":"ZA","type":"education","lineage":["https://openalex.org/I24027795"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Dustin van der Haar","raw_affiliation_strings":["Academy of Computer Science and Software Engineering, University of Johannesburg, Cnr University Road and Kingsway Avenue, Auckland Park, Johannesburg, 2092, Gauteng, South Africa"],"affiliations":[{"raw_affiliation_string":"Academy of Computer Science and Software Engineering, University of Johannesburg, Cnr University Road and Kingsway Avenue, Auckland Park, Johannesburg, 2092, Gauteng, South Africa","institution_ids":["https://openalex.org/I24027795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037252948"],"corresponding_institution_ids":["https://openalex.org/I24027795"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49609184,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"36","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.21279999613761902,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.21279999613761902,"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"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.1728000044822693,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.1581999957561493,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8504999876022339},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.843500018119812},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6061000227928162},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5687999725341797},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.46230000257492065},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.44999998807907104},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4399999976158142},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.3801000118255615},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.3774000108242035}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8504999876022339},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.843500018119812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7940000295639038},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6061000227928162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6028000116348267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5687999725341797},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.46230000257492065},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.44999998807907104},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4399999976158142},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3801000118255615},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3774000108242035},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.373199999332428},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.36500000953674316},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3375999927520752},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2971000075340271},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.2937999963760376},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C153914771","wikidata":"https://www.wikidata.org/wiki/Q5227343","display_name":"Data reduction","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25540000200271606},{"id":"https://openalex.org/C167651023","wikidata":"https://www.wikidata.org/wiki/Q1474611","display_name":"Plot (graphics)","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-032-03705-3_4","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-032-03705-3_4","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W2011301426","https://openalex.org/W2022718332","https://openalex.org/W2097117768","https://openalex.org/W2194775991","https://openalex.org/W2614326984","https://openalex.org/W2909693411","https://openalex.org/W2913500366","https://openalex.org/W2942170965","https://openalex.org/W2954187519","https://openalex.org/W2992308087","https://openalex.org/W3134717070","https://openalex.org/W3202608626","https://openalex.org/W4206758530","https://openalex.org/W4213189272","https://openalex.org/W4233367343","https://openalex.org/W4240485910","https://openalex.org/W4323046327","https://openalex.org/W4386159366","https://openalex.org/W4386391368","https://openalex.org/W4402740526","https://openalex.org/W6912515347"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-31T00:00:00"}
