基于深度CNN的腰果分级系统改进算法

A. Sivaranjani, S. Senthilrani, B. Ashokumar, A. Murugan
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引用次数: 7

摘要

随着分级、分类、分类等技术的不断进步,计算机视觉在农业领域越来越受欢迎。虽然腰果的技术有了很大的进步,但腰果的分级和分选在日常市场中仍然是一项艰巨的任务。在本研究中,我们讨论了基于计算机视觉的评分系统,并对深度卷积神经网络(CNN)进行了概述。深层CNN在许多图像分类应用中取得了巨大的成就。深度CNN本身提取图像的特征进行分类是其附加的优势。在这项工作中,考虑了各种参数来优化CNN。本文阐述了腰果分级的重要性,并提出了一种基于深度CNN的腰果计算机视觉分级系统框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improvised Algorithm For Computer Vision Based Cashew Grading System Using Deep CNN
Computer vision is becoming popular at the present days in agricultural area with an assortment of technological improvements for grading, sorting, classification. Though there are much technical advancement, cashew grading and sorting are still difficult task in daily market. In this research work we discussed about the computer vision based grading system and also an overview of deep Convolution Neural Network (CNN). The CNN with deep layer has tremendous achievement in many image classification applications. The deep CNN which itself extract the features of the image for classification was the added advantage. In this work the various parameters are considered for optimization of CNN. This work portrays the importance grading cashew nut and also proposed a framework for computer vision based grading system for cashew nut using deep CNN.
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