clustering an african hairstyle dataset using pca and k-means
Nicrocia, Teffo Phomolo, Adewale, Owolawi Pius, Diana, Pholo Moanda
–arXiv.org Artificial Intelligence
The adoption of digital transformation was not expressed in building an African face shape classifier. In this paper, an approach is presented that uses k-means to classify African women images. African women rely on beauty standards recommendations, personal preference, or the newest trends in hairstyles to decide on the appropriate hairstyle for them. In this paper, an approach is presented that uses K-means clustering to classify African women's images. In order to identify potential facial clusters, Haarcascade is used for feature-based training, and K-means clustering is applied for image classification.
arXiv.org Artificial Intelligence
May-25-2023
- Country:
- Africa
- Democratic Republic of the Congo > Kinshasa Province
- Kinshasa (0.04)
- Eritrea > Maekel
- Asmara (0.04)
- Nigeria > Ondo State
- Akure (0.04)
- Sierra Leone (0.04)
- South Africa
- Gauteng > Pretoria (0.05)
- Western Cape > Cape Town (0.04)
- Democratic Republic of the Congo > Kinshasa Province
- Asia > Taiwan
- Taiwan Province > Taipei (0.04)
- Europe > Italy (0.04)
- North America > United States
- Georgia > Clarke County > Athens (0.14)
- Africa
- Genre:
- Research Report (0.40)
- Technology: