Dataset Details
Title:
Crop Pest and Disease Dataset
Details:
The Dataset for Crop Pest and Disease Detection provides a large collection of high-resolution images captured from farms across Ghana to support AI research in agriculture. It addresses challenges like pest infestations and disease outbreaks that significantly impact yields. The dataset contains 24,881 raw images and 102,976 augmented images categorized into 22 classes across Cashew, Cassava, Maize, and Tomato crops. Each image was validated by expert plant virologists, and images were taken under various conditions and backgrounds. The dataset is made available under a CC BY 4.0 license, encouraging researchers to build and improve machine learning and deep learning models for crop health monitoring.
Mensah Kwabena, Patrick; Akoto-Adjepong, Vivian; Adu, Kwabena; Abra Ayidzoe, Mighty; Asare Bediako, Elvis; Nyarko-Boateng, Owusu; Boateng, Samuel; Fobi Donkor, Esther; Umar Bawah, Faiza; Songose Awarayi, Nicodemus; Nimbe, Peter; Kofi Nti, Isaac; Abdulai, Muntala; Roger Adjei, Remember; Opoku, Michael (2023), “Dataset for Crop Pest and Disease Detection”, Mendeley Data, V1, doi: 10.17632/bwh3zbpkpv.1