Popular GitHub Repositories for Animal Communication

An open protocol enabling communication and interoperability between opaque agentic applications.

OpenMMLab Pose Estimation Toolbox and Benchmark.

Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans

无线与深度学习结合的论文代码整理/Paper-with-Code-of-Wireless-communication-Based-on-DL

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

Amica is an open source interface for interactive communication with 3D characters with voice synthesis and speech recognition.

AgentNetworkProtocol(ANP) is an open source protocol for agent communication. Our vision is to define how agents connect with each other, building an open, secure, and efficient collaboration network for billions of intelligent agents.

Diffusion-based Portrait and Animal Animation

A data standard to enable right-of-way regulation, digital policy, geofencing, and two-way communication between mobility companies and public agencies worldwide.

Open protocol for communication between AI agents, applications, and humans.

Code repository for the Animal AI Olympics competition

a toolkit for pose estimation using deep learning

Turn detection for full-duplex dialogue communication

AIUI is a platform enabling seamless two-way verbal communication with AI.

Major Project - Sign Language To Text Conversion Using Python, Computer Vision and Machine Learning

On the Convergence of FedAvg on Non-IID Data

? ERA Connect by VYNECT™ — The evolution of secure WhatsApp automation ERA Connect is part of the VYNECT™ ecosystem, offering a premium solution for safe, ethical WhatsApp automation and testing using direct WebSocket communication. Automate conversations, simulate interactions, and manage messages with maximum speed, security, and stability

Reinforcement Learning approaches for learning communication in Multi Agent Systems.