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            <header>
                <identifier>oai:data.mendeley.com/mwdf2s328d.1</identifier>
                <datestamp>2024-06-11T18:35:25Z</datestamp>
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            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator>Chowdhury, Sudipta</dc:creator>
    <dc:title>BEANS</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>The dataset consists of over 500 images of beans (Phaseolus vulgaris L), categorized into two classes: &quot;good&quot; and &quot;bad.&quot; These images were captured using a Realme Narzo 20 Pro mobile camera against a black background under daylight conditions.

**Data Description:**

1. **Classes:**
   - Good: Represents healthy beans showcasing desirable characteristics such as uniform color, shape, and absence of defects, blemishes, or signs of damage or disease.
   - Bad: Encompasses beans exhibiting signs of damage, disease, or other undesirable traits such as discoloration, mold, deformities, or pest infestation.

2. **Image Collection:**
   - The dataset comprises over 500 images, with a substantial number representing both good and bad instances of beans.
   - Images were captured under consistent daylight conditions to ensure uniformity and minimize environmental variability.
   - A black background was utilized to enhance bean visibility and isolate the subject.

3. **Data Source:**
   - Images were captured using a Realme Narzo 20 Pro mobile camera, ensuring consistent image quality and resolution across the dataset.
   - Daylight conditions were chosen to provide natural lighting, reducing artificial effects on bean appearance.

4. **Annotation:**
   - Each image is labeled according to its class (good or bad), facilitating supervised learning tasks.
   - Annotations may include bounding boxes or masks outlining the bean area to aid in localization tasks.

5. **Data Preprocessing:**
   - Preprocessing techniques such as resizing, normalization, and background removal may have been applied to the images to enhance model performance and reduce computational complexity.
   - Metadata such as image resolution, format, and capture settings may accompany the dataset for reference.

6. **Data Distribution:**
   - The dataset maintains a balanced distribution between good and bad beans, ensuring equal representation of both classes.
   - Randomization techniques may have been employed during data collection and organization to mitigate biases in model training.

7. **Potential Applications:**
   - The dataset can be utilized for various machine learning tasks, including classification, object detection, and image segmentation, particularly in agricultural applications.
   - Applications may include automated sorting systems for bean quality control, disease detection, and yield optimization.

8. **Limitations:**
   - Despite efforts to ensure data consistency and quality, variations in lighting conditions, camera angles, and bean orientation may introduce some degree of variability.
   - The dataset primarily focuses on beans of the Phaseolus vulgaris L variety and may not generalize well to other bean varieties or environmental conditions.

</dc:description>
    <dc:subject>Biological Classification</dc:subject>
    <dc:subject>Characterization of Food</dc:subject>
    <dc:contributor>Sarkar, Tanmay</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/mwdf2s328d.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/mwdf2s328d.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dc:rights>http://creativecommons.org/licenses/by/4.0</dc:rights>
    <dc:relation>https://data.mendeley.com/datasets/mwdf2s328d</dc:relation>
    <dc:date>2024-06-11T18:35:25Z</dc:date>
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