基于深度神经网络的特有植物分类

Melih Öz, Alper Özcan
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引用次数: 0

摘要

特有植物是指那些原产于特定地理区域,在世界其他地方找不到的植物。这些植物对生物多样性、保护、文化意义和经济价值至关重要。土耳其有超过4000种本地植物。因此,这使土耳其成为欧洲最富有的国家。保护这个栖息地非常重要。这项研究的目的是概念化一个可能的应用程序,帮助个人识别特有物种使用相机捕获的图像。因此,有助于保护栖息地。本研究采用深度神经网络对土耳其23种特有生物多样性进行分类。为了符合本研究的目标,我们创建了一个包含253张图像的数据集来训练网络。该数据集可从github.com/melihoz/endemicdataset获取
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Endemic Plant Classification Using Deep Neural Networks
Endemic plants are those that are native to a specific geographic region and are found nowhere else in the world. These plants are crucial for biodiversity, conservation, cultural significance, and economic value. Turkey hosts more than 4000 endemic plants. Therefore, this makes Turkey the richest in Europe. Preserving this habitat holds importance. This study aims to conceptualize a possible application that helps individuals to identify endemic species using camera-captured images. Thus, aiding the preservation of the habitat. In this study, 23 selected species of Turkey’s endemic biodiversity are classified using Deep Neural Network built. In line with the objective of this study, a dataset containing 253 images is created to train the network. The dataset is available at: github.com/melihoz/endemicdataset
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