000			01431nam a22001817a 4500
003			NUST
040			_a0
082			_a621.382,ZAH
100			_aZaheer, Talha _9118354
245			_aDisease Detection In Wheat Crop (DDWC) / _cTalha Zaheer, Huma Kalsoom, Gulzar Lilla, Farhan Mustafa. (TCC-31 / BETE-56)
264			_aMCS, NUST _bRawalpindi _c2023
300			_a85 p
505			_aOur project aims to address the challenges faced by Pakistani farmers in identifying plant diseases quickly, leading to reduced crop quality and productivity. To achieve this, we propose the development of a cutting- edge smart phone app utilizing deep learning technology to accurately diagnose plant disease. The focus will be on wheat crops, and we will create our dataset of images to train a convolutional neural network. Our approach involves using transfer learning with the VGG16 architecture to achieve high accuracy and performance in disease identification. Through the implementation of our solution, we hope to empower farmers and increase agricultural productivity, contributing to a more sustainable and prosperous future for Pakistan. The project aims to revolutionize the agricultural industry in Pakistan by leveraging technology to improve plant disease diagnosis and management.
650			_aUG EE Project _9118090
690			_aTCC-31 / BETE-56 _9118237
700			_aSupervisor Dr. Alina Mirza _9118355
942			_2ddc _cTHE
999			_c603319 _d603319