Starred repositories
SCD: A Stacked Carton Dataset for Detection and Segmentation
Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.
Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.
Code and models for efficient training on the BigEarthNet dataset for Land Use Land Cover classification
😎 A curated list of awesome MLOps tools
[Book-2021] Practical MLOps O'Reilly Book
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning
Invoke is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The …
Methods and Implements of Deep Clustering
🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.
Code for the paper 'Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification'.
🎨 Color recognition & classification & detection on webcam stream / on video / on single image using K-Nearest Neighbors (KNN) is trained with color histogram features by OpenCV.
color recognition (convolutional neural network implemented in Keras)
Generate responsive pages and apps on HTML, Tailwind, Flutter and SwiftUI.
A CNN-RNN based model that identifies correlations between optical and SAR data and exports dense Normalized Difference Vegetation Index (NDVI) time-series of a static 6-day time resolution and can…
SENTIMENT ANALYSIS WITH DEEP LEARNING METHODS OF PUBLISHED TURKİSH TWEETS FOR GSM OPERATORS
Faster R-CNN for Open Images Dataset by Keras
Using neighborhood-based link prediction methods to predict new links that will occur in networks created from darts championship competitions
This repo covers the application of transfer learning methods using pre-trained networks.