基于快速rcnn的石榴病害检测与分类深度学习模型

A. Makandar, Syeda Bibi Javeriya
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引用次数: 0

摘要

印度是世界上最大的石榴生产国,石榴的利润很高。然而,由于温度变化、气候和暴雨等大气条件,石榴果实容易感染各种疾病,造成农业损失。卡纳塔克邦地区最常见的两种疾病是细菌性枯萎病和炭疽病,这两种疾病都会造成重大的生产损失。本文利用深度学习从定制训练模型中提取知识,对这两种疾病进行了检测和分类。为了克服传统方法,Faster-RCNN帮助我们更好地进行目标检测。关键词:深度学习,Faster-RCNN, Tensorflow细菌枯萎病,炭疽病,目标检测
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Faster-RCNN Based Deep Learning Model for Pomegranate Diseases Detection and Classification
India is the largest producer of pomegranates in the world which earns a high profit. However, due to atmospheric conditions such as temperature variations, climate, and heavy rains, pomegranate fruits become infected with various diseases, resulting in agricultural losses. The two most common diseases seen in the Karnataka region are bacterial blight and anthracnose, both of which cause a significant production loss. This paper has detected and classified these two diseases by extracting knowledge from custom trained models using Deep Learning. To overcome the traditional methods, Faster-RCNN helps us to do better object detection. Keyword : Deep Learning, Faster-RCNN, Tensorflow Bacterial blight, Anthracnose, Object detection.
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