Disease Detection In Wheat Crop (DDWC) / (Record no. 603319)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01431nam a22001817a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NUST |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | 0 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 621.382,ZAH |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Zaheer, Talha |
| 245 ## - TITLE STATEMENT | |
| Title | Disease Detection In Wheat Crop (DDWC) / |
| Statement of responsibility, etc. | Talha Zaheer, Huma Kalsoom, Gulzar Lilla, Farhan Mustafa. (TCC-31 / BETE-56) |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | MCS, NUST |
| Name of producer, publisher, distributor, manufacturer | Rawalpindi |
| Date of production, publication, distribution, manufacture, or copyright notice | 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 85 p |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Our 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | UG EE Project |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) | |
| Topical term or geographic name as entry element | TCC-31 / BETE-56 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervisor Dr. Alina Mirza |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
| Withdrawn status | Permanent Location | Current Location | Shelving location | Date acquired | Full call number | Barcode | Koha item type |
|---|---|---|---|---|---|---|---|
| Military College of Signals (MCS) | Military College of Signals (MCS) | Thesis | 10/04/2023 | 621.382,ZAH | MCSPTC-455 | Project Report |