Matches in SemOpenAlex for { <https://semopenalex.org/work/W2963503468> ?p ?o ?g. }
- W2963503468 endingPage "48" @default.
- W2963503468 startingPage "23" @default.
- W2963503468 abstract "With the ever-increasing load of satiating the agricultural demands, the transition of the orthodox methods into smart ones is inevitable. The agriculture sector for long has served as a momentous source of livelihood for many globally. It is arguably a major topic for nations of the development spectrum, contributing towards their export earnings and aiding in their GDP assessment. Thus, it is quite conspicuous that nations would work towards its expansion. In congruence, the burgeoning population and its demands have posed a threat to the environment due to extensive exploitation of resources, which in turn is escalating towards the downfall of the quality and quantity of agricultural produces requiring a 70% increment in the produces by 2050 for sustainability. To combat such hurdles, developed techniques are being employed. Through a survey of existing literature, this chapter provides a comprehensive overview of various image processing means that could come in handy for ameliorating the present scenario and shows their implied extension in the smart farming world." @default.
- W2963503468 created "2019-07-30" @default.
- W2963503468 creator A5037529623 @default.
- W2963503468 creator A5067877278 @default.
- W2963503468 date "2020-01-01" @default.
- W2963503468 modified "2023-09-25" @default.
- W2963503468 title "Image Processing Techniques Aiding Smart Agriculture" @default.
- W2963503468 cites W1484144136 @default.
- W2963503468 cites W1496809651 @default.
- W2963503468 cites W1597793043 @default.
- W2963503468 cites W1696827118 @default.
- W2963503468 cites W1892082890 @default.
- W2963503468 cites W1975940050 @default.
- W2963503468 cites W1979062633 @default.
- W2963503468 cites W1980180011 @default.
- W2963503468 cites W2002877084 @default.
- W2963503468 cites W2004469763 @default.
- W2963503468 cites W2007550651 @default.
- W2963503468 cites W2026253792 @default.
- W2963503468 cites W2028045291 @default.
- W2963503468 cites W2030365305 @default.
- W2963503468 cites W2032513939 @default.
- W2963503468 cites W2059166905 @default.
- W2963503468 cites W2061938824 @default.
- W2963503468 cites W2129644020 @default.
- W2963503468 cites W2131415551 @default.
- W2963503468 cites W2134974756 @default.
- W2963503468 cites W2171150461 @default.
- W2963503468 cites W2183320018 @default.
- W2963503468 cites W2184767666 @default.
- W2963503468 cites W2213623769 @default.
- W2963503468 cites W2252964880 @default.
- W2963503468 cites W2263566319 @default.
- W2963503468 cites W2463733399 @default.
- W2963503468 cites W2495597503 @default.
- W2963503468 cites W2510112041 @default.
- W2963503468 cites W2541216820 @default.
- W2963503468 cites W2543665758 @default.
- W2963503468 cites W2557206963 @default.
- W2963503468 cites W2558597124 @default.
- W2963503468 cites W2594479137 @default.
- W2963503468 cites W2596004444 @default.
- W2963503468 cites W2601692028 @default.
- W2963503468 cites W2603364874 @default.
- W2963503468 cites W2609151886 @default.
- W2963503468 cites W2621509397 @default.
- W2963503468 cites W2625680238 @default.
- W2963503468 cites W2730277950 @default.
- W2963503468 cites W2732084414 @default.
- W2963503468 cites W2761140038 @default.
- W2963503468 cites W2765938126 @default.
- W2963503468 cites W2783679175 @default.
- W2963503468 cites W2786087490 @default.
- W2963503468 cites W2786744169 @default.
- W2963503468 cites W2889984020 @default.
- W2963503468 cites W2891767313 @default.
- W2963503468 cites W2897204176 @default.
- W2963503468 cites W2901264480 @default.
- W2963503468 cites W2901813464 @default.
- W2963503468 cites W291468542 @default.
- W2963503468 cites W71648540 @default.
- W2963503468 doi "https://doi.org/10.4018/978-1-5225-9632-5.ch002" @default.
- W2963503468 hasPublicationYear "2020" @default.
- W2963503468 type Work @default.
- W2963503468 sameAs 2963503468 @default.
- W2963503468 citedByCount "2" @default.
- W2963503468 countsByYear W29635034682020 @default.
- W2963503468 countsByYear W29635034682021 @default.
- W2963503468 crossrefType "book-chapter" @default.
- W2963503468 hasAuthorship W2963503468A5037529623 @default.
- W2963503468 hasAuthorship W2963503468A5067877278 @default.
- W2963503468 hasConcept C10138342 @default.
- W2963503468 hasConcept C118518473 @default.
- W2963503468 hasConcept C134560507 @default.
- W2963503468 hasConcept C144024400 @default.
- W2963503468 hasConcept C144133560 @default.
- W2963503468 hasConcept C149923435 @default.
- W2963503468 hasConcept C162324750 @default.
- W2963503468 hasConcept C166957645 @default.
- W2963503468 hasConcept C175605778 @default.
- W2963503468 hasConcept C18903297 @default.
- W2963503468 hasConcept C205649164 @default.
- W2963503468 hasConcept C2781426361 @default.
- W2963503468 hasConcept C2908647359 @default.
- W2963503468 hasConcept C3987366 @default.
- W2963503468 hasConcept C47768531 @default.
- W2963503468 hasConcept C66204764 @default.
- W2963503468 hasConcept C86803240 @default.
- W2963503468 hasConceptScore W2963503468C10138342 @default.
- W2963503468 hasConceptScore W2963503468C118518473 @default.
- W2963503468 hasConceptScore W2963503468C134560507 @default.
- W2963503468 hasConceptScore W2963503468C144024400 @default.
- W2963503468 hasConceptScore W2963503468C144133560 @default.
- W2963503468 hasConceptScore W2963503468C149923435 @default.
- W2963503468 hasConceptScore W2963503468C162324750 @default.
- W2963503468 hasConceptScore W2963503468C166957645 @default.
- W2963503468 hasConceptScore W2963503468C175605778 @default.
- W2963503468 hasConceptScore W2963503468C18903297 @default.