Poultry Diseases Detection Dataset

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Poultry Diseases Detection Dataset

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Poultry Diseases Detection

Use Case

Poultry Diseases Detection

Description

Poultry Diseases Detection Dataset featuring high-quality JPEG images categorized into four classes: Coccidiosis, Salmonella, Newcastle disease, and Healthy poultry.

Description:

This dataset is designed for the detection and classification of poultry diseases. It includes images of poultry feces categorized into four classes: Coccidiosis, Salmonella, Newcastle disease, and Healthy poultry. The images are in JPEG format and organized into four separate directories, each representing one class.

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Dataset Structure:

Coccidiosis: Images showing symptoms of Coccidiosis in poultry.
Salmonella: Images showing symptoms of Salmonella infection.
Newcastle Disease: Images depicting Newcastle disease.
Healthy Poultry: Images of healthy poultry feces.

Details:

Format: JPEG images
Classes: 4 (Coccidiosis, Salmonella, Newcastle disease, Healthy)
Usage: Ideal for training machine learning models to identify and classify poultry diseases based on fecal images.

Applications:

Veterinary Diagnostics: Aid in automated disease detection in poultry farms.
Research: Support studies in veterinary medicine and animal husbandry.
AI Development: Enhance the development of robust AI models for disease detection.

Benefits:

Accuracy: High-quality annotated images ensure reliable training data.
Versatility: Suitable for various machine learning frameworks and algorithms.
Scalability: Can be used for both small-scale studies and large-scale industrial applications.