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JUDITH NJOKU's Projects

-face-and-facial-expression-detection-based-authenticated-zigbee-based-robo icon -face-and-facial-expression-detection-based-authenticated-zigbee-based-robo

In this project a robot that can be operated by authorized person or operator is implemented. For this purpose we use a face recognition system which is capable of identifying the authorized person which allows him to command and operate it. The face recognition system consists of a web based camera which captures the image of human and this image is processed in MATLAB software. After processing the image it generates the activation code for the robot to be operated. The hardware system is based on the ATMEL microcontroller and an Zigbee module. The system provides continuous visual monitoring through the small camera attached to the mobile robot, sending data to the control unit when necessary. Remote testing is done on the mobile robot for search and rescue missions via an established radio frequency (RF) communication using DIGI XBee RF module. Intelligent mobile robots and cooperative multi agent robotic systems can be very efficient tools to speed up search and research operations in remote areas. This prototype robot is capable of moving across area and remotely guided by a person who is directed and navigated using remote camera and computer.. Mobile robots using Zigbee protocol for the purpose of navigation using personal computer, implemented with wireless vision system for remote monitoring and control. Its main feature is its use of the Zigbee protocol as the communication medium between the mobile robot and the PC controller. The robot can be monitored only by authorized persons who are previously present in the database for security reasons. For this we utilize the Face recognition technology. It is a system which can automatically identify and verify the individuals face. Thus face and emotion recognition offers one of the most natural and less obtrusive bio metric measures of identification

10-steps-to-become-a-data-scientist icon 10-steps-to-become-a-data-scientist

📢 Ready to learn! you will learn 10 skills as data scientist:📚 Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.

agents icon agents

TF-Agents is a library for Reinforcement Learning in TensorFlow

amc-toolbox icon amc-toolbox

MATLAB toolbox for automatic modulation classifier development

amc_baby_models icon amc_baby_models

Automatic Modulation Classification implemented on different deep learning frameworks

augmentation_gan icon augmentation_gan

GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in COVID-19 Classification

augmentedautoencoder icon augmentedautoencoder

Official Code: Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

autoencoder icon autoencoder

Implementation of Semantic Hashing. Modified from Ruslan Salakhutdinov and Geoff Hinton's code of training Deep AutoEncoder

autoencoder-based-communication-system icon autoencoder-based-communication-system

Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/

autoencoderfiber icon autoencoderfiber

This shows how to use Autoencoders for learning constellations and receivers in fiber optical communications

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