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dc.contributor.authorDesai, Geeta-
dc.contributor.authorPratima, Kailash Chauhan (16ET01)-
dc.contributor.authorSarifakhatun, Hemaluddin Momin (17ET06)-
dc.contributor.authorPathan, Gausiya Rashid Khan (16ET05)-
dc.date.accessioned2021-10-22T05:12:26Z-
dc.date.available2021-10-22T05:12:26Z-
dc.date.issued2021-05-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3431-
dc.description.abstractAgriculture plays a vital role in the economic growth of any country. With the increase of population, frequent changes in climatic conditions and limited resources, it becomes a challenging task to fulfil the food requirement of the present population. Precision agriculture also known as smart farming have emerged as an innovative tool to address current challenges in agricultural sustainability Deep learning has brought huge improvement in the area of machine learning in general and most particularly in computer vision. The advancement of deep learning has been applied to various domain leading to tremendous achievement in the area of machine learning and computer vision. Only recent works have introduced applying deep learning to the field of using computer in agriculture The need for food production and food plant is of utmost importance for human society to meet the growing demands of an increased population. Automation plant detection using plant images was Originally tackled using traditional machine learning detection using plant images in limited accuracy result and limited scope. Using deep learning in plant detection made it possible to produce higher prediction accuracyen_US
dc.language.isoenen_US
dc.publisherAIKTCen_US
dc.subjectProject Report - EXTCen_US
dc.titleCrop classification using machine learningen_US
dc.typeOtheren_US
Appears in Collections:EXTC Engineering - Project Reports

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