Popular GitHub Repositories for Colour Schemes

A curated list of watermarking schemes for generative AI models

Neural Radiance Fields from a Single Colour Event Camera [CVPR 2023]

An Enhanced Implementation of the Colour Transfer Method Proposed by E Reinhard et al.

Car's plate detection and car's colour detection with YOLO5 and LPRnet

Description and applications of OpenAI's paper about DALL-E (2021) and implementation of other (CLIP-guided) zero-shot text-to-image generation schemes

Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradients. To achieve robustness to users dropping out, existing practical privacy-preserving federated learning schemes are based on (t, N)-threshold secret sharing. Such schemes rely on a strong assumption to guarantee security: the threshold t must be greater than half of the number of users. The assumption is so rigorous that in some scenarios the schemes may not be appropriate. Motivated by the issue, we first introduce membership proof for federated learning, which leverages cryptographic accumulators to generate membership proofs by accumulating users IDs. The proofs are issued in a public blockchain for users to verify. With membership proof, we propose a privacy-preserving federated learning

Code for "Adaptive Gradient Quantization for Data-Parallel SGD", published in NeurIPS 2020.

PyScreen is an AI-powered tool that extracts, analyzes, and visualizes data from screen recordings. It leverages advanced computer vision, text processing, and AI techniques to provide valuable insights such as dominant color schemes, frequently used words, and content descriptions using OpenAI's GPT-4 model.

The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).

Python programs for filtering/segmenting vegetation from bare-Earth points in point clouds with RGB colour. This repo is supplementary to my AGU presentation in December 2021 and my manuscript published in Remote Sensing in June 2024.

Federated Learning (FL) is a collaborative machine learning approach that enables decentralized data processing. Instead of collecting and storing data in a central server, FL trains machine learning models directly on devices or servers where the data resides, enhancing privacy and security.

? Generates a unique random tree artwork from a given seed

Generative Art project to turn text into unique and sharable colour grids.

POC that Creates an image consisting of horizontal slices of the average colour of frames in a video

Saarthi is an AI-powered, voice-first assistant that helps citizens discover and understand government schemes with face authentication, secure PII handling, and a Streamlit UI powered by LangGraph and local LLMs.

slice sampling with option to add constraints

A comparative analysis of training schemes for voice style transfer in spanish.

Comparing different quantization schemes in terms of inference speed for ResNet50.

A multi-agent LLM app with conversational agents, which suggests relevent government schemes to users.

JanaVaani is a voice-based AI assistant that empowers citizens to access government schemes, report civic issues, and get real-time help through a simple phone call.