Kabir Hasnain, Juthi Taslima, Islam Md Tarequl, Rahman Md Wahidur, Khan Rahat
Department of Computer Science and Engineering, Khwaja Yunus Ali University, Sirajganj, Bangladesh.
Department of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Data Brief. 2023 Nov 29;52:109872. doi: 10.1016/j.dib.2023.109872. eCollection 2024 Feb.
The "WaterHyacinth" dataset, a recently gathered collection of images featuring four distinct species of Water hyacinth from different regions of Bangladesh, is presented in this article. There are four different classifications: , and . The collection consists of 1790 original images and in addition 4050 augmented photos of Water hyacinth species. Every original picture was captured with the appropriate background and in sufficient natural light. Every image was correctly placed in its corresponding subfolder, providing optimal use of the pictures by various machine learning and deep learning models. Researchers could make major progress in agriculture, environmental monitoring, aquatic science, and remote sensing domains by utilizing this enormous dataset and various machine learning and deep learning approaches. In addition to opening opportunities for significant developments in these domains, it offers an essential asset for further study.
本文介绍了“水葫芦”数据集,这是最近收集的一组图像,展示了来自孟加拉国不同地区的四种不同水葫芦物种。有四种不同的分类: ,和 。该数据集包含1790张原始图像,此外还有4050张水葫芦物种的增强照片。每张原始图片都是在合适的背景和充足的自然光下拍摄的。每张图像都被正确地放置在其相应的子文件夹中,以便各种机器学习和深度学习模型能够最佳地使用这些图片。通过利用这个庞大的数据集以及各种机器学习和深度学习方法,研究人员可以在农业、环境监测、水生科学和遥感领域取得重大进展。除了为这些领域的重大发展带来机遇外,它还为进一步研究提供了重要资源。