Popular GitHub Repositories for Moving

AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.

Find big moving stocks before they move using machine learning and anomaly detection

Simple and Efficient Tensorflow implementations of NER models with tf.estimator and tf.data

Official implementation of the paper: MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera (CVPR 2021)

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild. ECCV 2022.

An Unsupervised Learning Framework for Moving Object Detection From Videos

Implementation of Mega, the Single-head Attention with Multi-headed EMA architecture that currently holds SOTA on Long Range Arena

[ICRA2024] RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud

HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems

[CVPR 2021] DeFMO: Deblurring and Shape Recovery of Fast Moving Objects

Algorithm for prioritized multi-agent path finding (MAPF) in grid-worlds. Moves into arbitrary directions are allowed (each agent is allowed to follow any-angle path on the grid). Timeline is continuous, i.e. action durations are not explicitly discretized into timesteps. Different agents' size and moving speed are supported. Planning is carried out in (x, y, \theta) configuration space, i.e. agents' orientation are taken into account.

MobileNet-SSD(MobileNetSSD) + Neural Compute Stick(NCS) Faster than YoloV2 + Explosion speed by RaspberryPi · Multiple moving object detection with high accuracy.

Differentiable electromagnetics simulation library for moving point charges built on JAX

This repository hosts the implementation of autonomous vehicle navigation using RL techniques, with a specific emphasis on Deep Q-Networks (DQN) and Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithms. We focus on training a TurtleBot3 robot to navigate autonomously through environments while intelligently avoiding moving obstacles.

This repository provides the companion Jupyter Notebooks for the book Context-Engineering for Multi-Agent Systems. It technically details the progressive construction of a Context Engine moving from simple prompts to foundational concepts to a production-ready system semantic blueprint. The code is a guide to building Multi-Agent Systems (MAS)

ai42z is an innovative framework designed to transform Large Language Models (LLMs) into autonomous, self-learning AI agents. The framework stands out by enabling AI agents to build and maintain a cumulative knowledge base through real-world experience, moving beyond the limitations of traditional static instruction-following systems.

Balancing, Moving, and Traversing Slopes with a Two-Wheel Robot using Deep Reinforcement Learning

In this repository, we focus on video frame prediction the task of predicting future frames given a set of past frames. We present an Adversarial Spatio-Temporal Convolutional LSTM architecture to predict the future frames of the Moving MNIST Dataset. We evaluate the model on long-term future frame prediction and its performance of the model on out-of-domain inputs by providing sequences on which the model was not trained.

A quantitative trading strategy backtester with an interactive dashboard. Enables users to implement, test, and visualise trading strategies using historical market data, featuring customisable parameters and key performance metrics. Developed with Python and Polars.