Popular GitHub Repositories for Mouse Movement

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

A Unity library for common movement AI

Artificial Intelligence framework for games based on libGDX or not. Features: Steering Behaviors, Formation Motion, Pathfinding, Behavior Trees and Finite State Machines

Use NLP to predict stock price movement associated with news

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

A python package for simulating movement and spatial cell types (e.g. place cells, grid cells) in continuous environments.

Using Machine Learning to predict the type of exercise from movement data

An AI model used to help with the workout session by keeping track of counts and movement.

Developed an AI-based system to control the mouse cursor using Python and OpenCV with the real-time camera. Fingertip location is mapped to RGB images to control the mouse cursor.

Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning Approach. TPAMI 2018.

Real time face landmarking using decision trees and NN autoencoders

The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using transaction data from the Limit Order Book (LOB).

Dynamic movement primitives (DMPs) are a method of trajectory control/planning from Stefan Schaal’s lab. Complex movements have long been thought to be composed of sets of primitive action ‘building blocks’ executed in sequence and \ or in parallel, and DMPs are a proposed mathematical formalization of these primitives. The difference between DMPs and previously proposed building blocks is that each DMP is a nonlinear dynamical system. The basic idea is that you take a dynamical system with well specified, stable behavior and add another term that makes it follow some interesting trajectory as it goes about its business. The DMP differential equations (Transformation System, Canonical System, Non-linear Function) realize a general way of generating point-to-point movements. Imitation learning using linear regression is performed to com

Maximum likelihood analysis Of animal MovemENT behavior Using multivariate Hidden Markov Models

Research project on coordinated movement of AI made with Unity.

Movement Primitive Diffusion (MPD) is a diffusion-based imitation learning method for high-quality robotic motion generation that focuses on gentle manipulation of deformable objects.

The Mobilise-D algorithm toolbox - Implemented in Python

Multi Atlas Segmentation and Morphometric analysis toolkit (MASMAT) for mouse brain MRI

Cutting-edge Python software utilizing neural networks and machine learning for precise hand movement tracking

Proof of concept code from Gretel.ai and Illumina using generative neural networks to create synthetic versions of mouse genotype and phenotype data.