CNN based techniques for Detecting Anomalies in the Crop

dc.contributor.authorRimsha Urooj , Shifa Allah Baksh , Fatima Batool
dc.contributor.authorFA17-BSE-154 , FA17-BSE-164 , FA17-BSE-017
dc.contributor.authorDr. Zeeshan Gillani
dc.contributor.authorLHR TP 7027
dc.date.accessioned2026-02-19T06:13:58Z
dc.date.issued2021
dc.description.abstractThe population across the globe is increasing at an alarming rate across the globe. This is giving rise to many challenges and one of the primary challenges is to feed an ever-increasing population with the same resources availed. This will lead to a food security and food crisis if we are not able to adapt our farming methods to modern technologies. With the advancement in computer vision techniques by using advanced CNN-based methods we can now analyse crops to detect anomalies in the crop. These applications could provide a foundation for the development of expertise aid or automatic screening tools. Such tools could contribute to further sustainable agricultural traditions and greater food production safety.
dc.identifier.urihttps://repository.cuilahore.edu.pk/handle/123456789/1925
dc.language.isoen
dc.publisherLibrary Information Services, COMSATS University Islamabad, Lahore Campus
dc.relation.ispartofseriesLHR TP 7027
dc.subjectTECHNOLOGY::Information technology::Computer science
dc.subjectDr. Zeeshan Gillani
dc.titleCNN based techniques for Detecting Anomalies in the Crop
dc.typeThesis

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