使用CNN和Inception V3算法的Alstonia树检测

Mamatha Balipa, Ashton Castalino
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引用次数: 1

摘要

Alstonia tree(Pale tree)是一种树皮提取物用于药用的树,很难识别。由于树木的种类繁多,以及方向、视点、背景、杂波等因素的差异,很难利用树木的图像对不同的树木进行识别和分类。植物和树木的识别是至关重要的,因为它使我们能够收集有关不同物种的相关信息,以支持特定的应用。在这里,使用预训练的Inception V3模型和卷积神经网络(CNN)方法来检测和分类树。CNN模型比传统方法提供更高的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Alstonia Tree Detection using CNN and Inception V3 Algorithms
Alstonia tree(Pale tree) is a tree whose bark extract is used for medicinal purpose and is difficult to identify. Due to the existence of wide variety of trees, as well as differences in orientation, viewpoint, background, clutter, and other factors, it is difficult to identify and categorize distinct trees using their images. Plant and tree identification is crucial since it allows us to collect the relevant information about various species to support a specific application. Here, the pretrained Inception V3 model and the Convolutional Neural Network (CNN) method are used to detect and classify trees. CNN models offer higher accuracy rates than conventional methods.
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