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Machine Learning and image processing in leaf disease detection

عنوان مقاله: Machine Learning and image processing in leaf disease detection
شناسه ملی مقاله: SETIET04_021
منتشر شده در چهارمین کنفرانس بین المللی علوم، مهندسی، و نقش تکنولوژی در کسب و کارهای نوین در سال 1402
مشخصات نویسندگان مقاله:

Pezhman Golshanrad - Sharif University of Technology (International Campus) Department of Computer Eng.

خلاصه مقاله:
Plant diseases have significant negative impacts on agricultural production and economicoutcomes, leading to reduced quality and quantity of crops. The detection of plant diseases hasbecome an increasingly important area of focus in monitoring large fields of crops. Farmersoften face challenges when transitioning from one disease control strategy to another.Traditionally, experts rely on naked eye observation for disease detection and identification. Thispaper emphasizes the need for a simple plant leaf disease detection system to driveadvancements in agriculture. Early detection of crop health and diseases can enable effectivedisease control through proper management strategies, ultimately improving crop productivity.The paper also evaluates the advantages and limitations of various potential methods, includingimage acquisition, image pre-processing, feature extraction, and neural network-basedclassification.

کلمات کلیدی:
Disease detection, Image acquisition, pre-processing, features extraction.

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1722827/