✳flâneur — a map of the web's best reading
How to cluster images based on visual similarity | by Gabe Flomo | Towards Data Science
towardsdatascience.com · 1,545 words · saved by 1 readers
Use a pre-trained neural network for feature extraction and cluster images using K-means.
How to cluster images based on visual similarity | Towards Data Science Machine Learning How to cluster images based on visual similarity Use a pre-trained neural network for feature extraction and cluster images using K-means. Gabe Flomo Sep 29, 2020 5 min read Share Photo by Pietro Jeng on Unsplash Objective In this tutorial, I’m going to walk you through using a pre-trained neural network to extract a feature vector from images and cluster the images based on how similar the feature vectors are. The model The pre-trained model that will be used in this tutorial is the VGG16 convolutio
Explore this link on the map →saved by
related reading
- Feature Visualizationdistill.pub
- Feature Visualizationdistill.pub
- GitHub - facebookresearch/faiss: A library for efficient similarity search and clustering of dense vectors. · GitHubgithub.com
- Vector embeddings | OpenAI APIdevelopers.openai.com
- The Illustrated Word2vec – Jay Alammar – Visualizing machine learning one concept at a time.jalammar.github.io
- k-means clustering - Wikipediaen.wikipedia.org
- Convolutional Neural Network (CNN) | TensorFlow Coretensorflow.org
- Faiss: A library for efficient similarity search - Engineering at Metaengineering.fb.com
- Vector embeddings | OpenAI APIplatform.openai.com
- GitHub - zhoushengisnoob/DeepClustering: Methods and Implements of Deep Clustering · GitHubgithub.com
- Fast and Simple Image Search with Foundation Models - Ivan Zhouivanzhou.me
- Convex hull, Image processing, Image Classification, Image retrieval, Shape detectiondiva-portal.org