Both methods were implemented using Python libraries, with modelling choices guided by standard evaluation ... We calculated document similarity using cosine distance and applied a hybrid clustering ...

It's a Python application that sorts images by their similarity based on ConvNext deep learning features and HSV histogram comparison. Embeddings are pre-clustered with K-Means. FAISS index assigned ...

K-means is one of the most simple and popular clustering algorithms, which implemented as a standard clustering method in most of machine learning researches. The goal of K-means clustering is finding ...

Machine learning (ML) has emerged as a pillar across many industries, improving efficiency and productivity in a wide range of applications. As more organizations utilize cloud services to perform ...