Arman10121995

-Newell-and-Lee-Evaporator-design-and-control

• Modeling of an Evaporator in Matlab and Simulink • Performed the RGA analysis to apply PID controllers for controlling the MIMO system.

-Temperature-control-TC-Lab-using-Kalman-filter

• Modeling of TC Lab (two temperature sensors and heaters mounted on Aurdino) in Matlab and Simulink. • Implementation of Kalman filter and Extended Kalman filter to estimate state using sensor fusion. • Designed an integral Full State feedback controller to maintain the temperature at the desired set point.

A-Hackers-AI-Voice-Assistant

A hackers AI voice assistant, built using Python and PyTorch.

android-as-monitor-linux

This script will help you use your android device as a second monitor

Arman10121995

Config files for my GitHub profile.

beamer-ovgu

Latex Beamer Vorlage für die OVGU

CPU_load_via_ROS_Docker_Shellscript

A repository for ROS, Docker and Shell Script example

demo-repo

Demo for Github Intro Video.

Dynamic-Hand-gesture-Recognition-Mediapipe-LSTM-

Dynamic Hand gesture Recognition using Mediapipe holistic model for detection and feature extraction and LSTM for temporal dependency and classification

Face_recognition_Facenet_VggFace_Mtcnn_yoloface_SVM

A Face Recognition System using Mtcnn/YoloV3Face for face detection

Arman10121995/-Newell-and-Lee-Evaporator-design-and-control

• Modeling of an Evaporator in Matlab and Simulink • Performed the RGA analysis to apply PID controllers for controlling the MIMO system.

Arman10121995/-Temperature-control-TC-Lab-using-Kalman-filter

• Modeling of TC Lab (two temperature sensors and heaters mounted on Aurdino) in Matlab and Simulink. • Implementation of Kalman filter and Extended Kalman filter to estimate state using sensor fusion. • Designed an integral Full State feedback controller to maintain the temperature at the desired set point.

Arman10121995/A-Hackers-AI-Voice-Assistant

A hackers AI voice assistant, built using Python and PyTorch.

Arman10121995/android-as-monitor-linux

This script will help you use your android device as a second monitor

Arman10121995/Arman10121995

Config files for my GitHub profile.

Arman10121995/beamer-ovgu

Latex Beamer Vorlage für die OVGU

Arman10121995/CPU_load_via_ROS_Docker_Shellscript

A repository for ROS, Docker and Shell Script example

Arman10121995/demo-repo

Demo for Github Intro Video.

Arman10121995/Dynamic-Hand-gesture-Recognition-Mediapipe-LSTM-

Dynamic Hand gesture Recognition using Mediapipe holistic model for detection and feature extraction and LSTM for temporal dependency and classification

Arman10121995/Face_recognition_Facenet_VggFace_Mtcnn_yoloface_SVM

A Face Recognition System using Mtcnn/YoloV3Face for face detection

Arman10121995/github-slideshow

A robot powered training repository :robot:

Arman10121995/github-upload

Arman10121995/hand-gesture-recognition-using-mediapipe

MediaPipe(Python版)を用いて手の姿勢推定を行い、検出したキーポイントを用いて、簡易なMLPでハンドサインとフィンガージェスチャーを認識するサンプルプログラムです。（Estimate hand pose using MediaPipe(Python version). This is a sample program that recognizes hand signs and finger gestures with a simple MLP using the detected key points.）

Arman10121995/Hand_Gesture_Recognition

Dynamic Hand Gesture Recognition using Mediapipe and LSTM

Arman10121995/Image-Classification-using-CNN-for-Imagenette-Imagewoof-detaset

Here I tried to classify two data set by Cpnvolution Newral Network (CNN) using Keras & tenser flow:

Arman10121995/imagenette

A smaller subset of 10 easily classified classes from Imagenet, and a little more French

Arman10121995/Implementation-of-a-path-following-controller-on-unmanned-ground-vehicle

Designing a safe path for an unmanned vehicle is a crucial problem. The path should be not only obstacle free but also take into account the vehicle dynamics so that the path is feasible. Once the path is generated a path following controller should be able to execute this path driving the vehicle from certain start point to final destination point. Working in a group of 2 students, the aim of this project (given the obstacle free path) is to : 1. Define the working environment (start point, end points and obstacles) 2. Implement a path following model predictive controller on a ground vehicle Hamster (see figure). 3. Prepare a presentation for the achieved tasks Subject areas: Robotics, Optimal Control, Path Planning, Programming

Arman10121995/L2CS-Net

The official PyTorch implementation of L2CS-Net

Arman10121995/linkedin-skill-assessments-quizzes

Full reference of LinkedIn answers 2022 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers

Arman10121995/markdown-portfolio

Arman10121995/Safety-and-Security-analysis-and-assessment-of-Autonomous-vehicles-

Arman10121995/self-driving-car-specialization

Self -driving cars specialization by the university of toronto at coursera

Arman10121995/Self_Driving_Car_specialization

Assignments and notes for the Self Driving Cars course offered by University of Toronto on Coursera

Arman10121995/Spoon-Knife

This repo is for demonstration purposes only.

Arman10121995/Unit-Commitment-using-Dynamic-Programming

We performed Unit commitment which is the most economical and cost-efficient way for power generation. • Considers power consumption at different times and different constraints of the power plants • Predicts sequence of enabling and disabling the generating units intelligently • Minimize the cost of generating units • Reduces the amount of fuel consumption and hence is more eco-friendly • Increase the efficiency of the entire process all of the above was performed using a dynamic programming algorithm which is • Conventional algorithm process for optimization • Divide into multiple steps or stages • Use recursive solution procedure

Arman10121995/usage--ROS

Arman10121995/yolov3

YOLOv3 in PyTorch > ONNX > CoreML > TFLite