sharifipeyman

sharifipeyman's Stars

• iman-sharifi-ghb/Simulation-of-3DOF-Manipulator-on-6DoF-Satellite-using-Newtonian-Lagrangian-and-Quaternions-Methods

  Language:MATLAB2

• iman-sharifi-ghb/Retrospective-Cost-Adaptive-Controller-using-Recursive-Least-Square

  Language:MATLAB2

• iman-sharifi-ghb/PID-Tuning-using-Genetic-and-Particle-Swarm-Optimization

  Offline Tuning PID gains in a given system using Heuristic Methods, including Genetic Algorithm andParticle Swarm Optimization

  Language:MATLAB8

• iman-sharifi-ghb/Quadcopter-PID-Control-in-V-REP

  Control Quadcopter using PID Controller in Vrep CoppeliaSim Software with Python

  Language:Python31

• iman-sharifi-ghb/Double-Inverted-Pendulums-Control-Using-State-Feedback

  Language:MATLAB4

• iman-sharifi-ghb/Inverted-Pendulum-Control-using-state-feedback-Controller-and-observer

  Language:MATLAB3

• iman-sharifi-ghb/Ball-and-Beam-Control-using-State-Feedback-Controller-Observer-and-descrete-Controller

  Language:MATLAB31

• iman-sharifi-ghb/Modeling-Simulation-Design-and-Fabrication-of-2-wheel-mobile-balanced-robot-2WMBR

  Modeling a Mobile Robot using Advanced Dynamics Methods, Design & Simulation using Matlab and SolidWorks, Control using PID Controller, and Implemetation using Arduino UNO, Kalman Filter, and DC Motors..

  Language:MATLAB3

• iman-sharifi-ghb/CNN-Street-View-House-Number-Detection-SVHN

  We use Convelutional Neural Networks (CNN), as a Deep Learning paradigm, to detect the house numbers using the MNIST dataset.

  Language:Jupyter Notebook2

• iman-sharifi-ghb/Symbolic-Reinforcement-Learning-Prolog-Programming

  Safe Q-Learning via a Symbolic Logical Programming (Prolog) paradigm in Maze Gridworld.

  Language:Python2

• iman-sharifi-ghb/Inductive-Logic-Programming-ILP-using-Prolog-Programming-Aleph-Metagol-in-Maze

  Extract Symbolic Rules using Background Knowledge and Environement Setting to find the State Transition rules in the Maze gridworld.

  Language:Prolog3

• iman-sharifi-ghb/Self-Tuning-PID-Control-using-Reinforcement-Learning-Based-Neural-Network

  Novel adaptive tuning of the PID gains using an Actor-Critic-based Neural Network for Attitude Control of a 6-Dof, 4-motor Robot

  Language:Python91

• iman-sharifi-ghb/Video-Synopsis-Summarization-Car-Detection-Tracking

  Detection, Counting, Tracking, and Summarization of the Vehicles using Computer Vision algorithms in a video camera recorded on a highway.

  Language:Jupyter Notebook5

• iman-sharifi-ghb/Camera-Operations-Homography-and-Fundamental-Matrix-Using-SIFT-KNN-RANSAC-Algorithms

  SIFT, SURF, and ORB detector to extract the keypoints like corners. Fundumental Matrix and Homographical Transformation for Panorama Images.

  Language:Jupyter Notebook2

• iman-sharifi-ghb/Histogram-Oriented-Gradients-HOG-Supported-Vector-Machine-SVM-Face-Detection

  Extract features from the Stanford Dataset using Histogram of Oriented Gradients (HOG) and use Supported Vector Machine (SVM) to map the features to the assigned labels. Next, use Non-Maximum Suppression and Heatmap method to find the best bounding box on the face.

  Language:Jupyter Notebook3

• iman-sharifi-ghb/Quadcopter-Trajectory-Tracking-using-Adaptive-Nonlinear-Algorithms

  PID, LQR, Feedback Linearization, Backstepping, Sliding Mode, and Model Reference Adaptive Control for 6-DoF Robot Control

  Language:MATLAB586

• iman-sharifi-ghb/Function-Approximation-and-Adaptive-PID-Gain-Tuning-using-Neural-Networks-and-Reinforcement-Learning

  System Identification and Self-Tuning PID Control using NN

  Language:MATLAB646

• iman-sharifi-ghb/Trajectory-Tracking-of-8DoF-Tiltrotor-via-Fuzzy-Sliding-Mode-Control-with-Fuzzy-Identification

  Tiltrotor Control and System Identification using Fuzzy C-Means Clustering.

  Language:MATLAB91