Download Report IEEE DataPort : Almond Varieties Dataset — Image Collection for Classification and Varietal Identification - 2025
JPG (ZIP), PNG (ZIP) by Mustafa Yurdakul, Şakir Taşdemir
Information
Format: JPG (ZIP), PNG (ZIP) Publisher: IEEE DataPort Publication Date of the Electronic Edition: 11/12/2025
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ISBN: 10.21227/3gd9-ez60
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Description
This dataset contains high-resolution images of almond (Prunus dulcis) varieties collected for research on machine learning-based classification and varietal identification. The images were captured under controlled lighting conditions using a consistent setup to ensure uniform quality and minimal variability caused by external factors. Each image corresponds to a specific almond variety, and annotations include class labels representing the respective types.The dataset was originally published on Kaggle (https://www.kaggle.com/datasets/mahyeks/almond-varieties) and is associated with the article “Automatic classification of almond varieties using deep learning techniques” published in European Food Research and Technology (Springer, 2024). This IEEE DataPort version serves as an archived and citable copy for long-term availability and reproducibility in research.Researchers can use this dataset for tasks such as:Image classification and feature extraction,Model benchmarking for agricultural or food quality studies,Cross-domain analysis with other agricultural image datasets.All images are provided in JPEG format, and the dataset includes labeled folders for each almond variety. A brief metadata file describes the image acquisition setup, number of samples per class, and image resolution details.
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