RGB-colored; deep learning; Agriculture; Visual dataset; Automated harvesting; Paddy Disease classification;
The "Paddy Field Dataset Captured in Palakkad District, Kerala, India" is a comprehensive collection of geospatial and attribute data specifically focused on paddy cultivation within the Palakkad district of the Kerala state in India. This dataset encompasses a wide range of information related to paddy fields, including their spatial distribution, size, crop varieties cultivated, land management practices, and relevant contextual factors. Geographic Information System (GIS) technology has captured accurate geospatial coordinates, enabling precise mapping and analysis.
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The "Paddy Disease Dataset" represents a comprehensive collection of data related to various diseases commonly found in paddy crops. Paddy, or rice, is a staple crop crucial for global food security. However, paddy crops are susceptible to a range of diseases that can significantly impact yield and quality. This dataset encompasses a diverse array of disease-related information, including disease types, symptoms, geographical distribution, severity levels, and potential management strategies.
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Indian Rice Disease dataset (IRDD) contains rice leaf images of two classes namely BrownSpot and Healthy. The images are taken under various lightning conditions. Some images contain dew drops on the leaves. The rice leaf images are gatherd from fields in West Bengal, India. These images have been taken using smartphone camera by the project team members of IIIT Kalyani and IIT Kharagpur. The images are annotated and verified by the domain experts. This datset is a part of the project entitled "AI for Agriculture and Food Sustainability" funded by MeitY, Govt of India.
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