Flower breed detection and giving details of that breed with the suggestion of cultivation processes and the way of taking care is important for flower cultivation, breed invention, and the flower business. Among all the local flowers in Bangladesh, the rose is one of the most popular and demanded flowers. Roses are the most desirable flower not only in Bangladesh but also throughout the world. Roses can be used for many other purposes apart from decoration. As roses have a great demand in the flower business so rose breed detection will be very essential. However, there is no remarkable work for breed detection of a particular flower unlike the classification of different flowers. In this research, we have proposed a model to detect rose breeds from images using transfer learning techniques. For such work in flowers, resources are not enough in image processing and classification, so we needed a large dataset of the massive number of images to train our model. we have used 1939 raw images of five different breeds and we have generated 9306 images for the training dataset and 388 images for the testing dataset to validate the model using augmentation. We have applied four transfer learning models in this research, which are Inception V3, ResNet50, Xception, and VGG16. Among these four models, VGG16 achieved the highest accuracy of 99%, which is an excellent outcome. Breed detection of a rose by using transfer learning methods is the first work on breed detection of a particular flower that is publicly available according to the study.
翻译:花卉品种检测并提供该品种的详情以及种植和护理的建议对花卉种植、品种发明和花卉贸易至关重要。在孟加拉国的所有本地花卉中,玫瑰是最受欢迎和最受需求的花卉之一。 玫瑰不仅在孟加拉国,而且在全世界范围内都是最理想的花卉。 玫瑰除了装饰之外还可以用于许多其他用途。由于玫瑰在花卉行业中需求量很大,因此玫瑰品种检测将非常重要。然而,与不同花卉的分类相比,特定花卉的品种检测没有太多的研究可供参考。在这项研究中,我们提出了使用转移学习技术从图像中检测玫瑰品种的模型。在花卉方面,没有足够的资源进行图像处理和分类,因此我们需要大量图像的数据集来训练我们的模型。我们使用了五种不同品种的1939张原始图像,并使用了数据增强技术生成了9306张训练数据集和388张测试数据集来验证模型。我们应用了四个转移学习模型,分别是Inception V3,ResNet50,Xception和VGG16。在这四个模型中,VGG16实现了最高的99%准确率,这是一个很好的结果。根据该研究,使用转移学习方法进行特定花卉的品种检测是公开可用的首个研究。