A Comprehensive Augmented Image Dataset of Tomato Insect Pests for Deep Learning-Based Detection

Description

This dataset consists of images representing six distinct categories of common agricultural pests. The classes included in this dataset are: Cotton Bollworm Oriental Fruit Fly Peach Aphid Silverleaf Whitefly Thrips Two-spotted Spider Mite Data Collection and Processing: The dataset is a compilation of original images curated from open-access repositories and web scraping. A significant portion of the base images was derived from existing Mendeley Data repositories (cited below) and Google Images. To enhance the dataset's utility for Deep Learning and Computer Vision tasks, data augmentation techniques were applied. The augmentation process involved operations such as rotation (90°, 180°, 270°), horizontal and vertical flipping, and scaling to increase the sample size and diversity of the data. Organization: The dataset is organized into six folders, each corresponding to a specific pest category. This dataset is suitable for training and testing machine learning models in the field of precision agriculture and automated pest detection. References / Data Sources: We acknowledge the authors of the original datasets used in this compilation: [A database of eight common tomato pest images] - Available at: [https://data.mendeley.com/datasets/s62zm6djd2/1] [TOM2024] - Available at: [https://data.mendeley.com/datasets/3d4yg89rtr/1]

Institutions

• Daffodil International University

  Dhaka Division, Dhaka

Categories

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