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Name: JUDITH NJOKU
Type: User
Bio: I am a self taught Front-end developer and Machine learning engineer, veraciously seeking to learn more
Location: Nigeria
Blog: judithnjoku.com
Name: JUDITH NJOKU
Type: User
Bio: I am a self taught Front-end developer and Machine learning engineer, veraciously seeking to learn more
Location: Nigeria
Blog: judithnjoku.com
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
Deep Learning for Massive MIMO with 1-Bit ADCs
📢 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.
These are the instructions for "100 Days of ML Code" By Siraj Raval on Youtube
Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).
We have proposed a novel pilot decontamination scheme which combines the two existing schemes: SPRS and WGC-PD scheme.
Adaptive Modulation using k-NN classification for OFDM system
Chainer implementation of adversarial autoencoder (AAE)
A wizard's guide to Adversarial Autoencoders
TF-Agents is a library for Reinforcement Learning in TensorFlow
Hands-On Machine Learning with Scikit-Learn & TensorFlow (O'Reilly)
MATLAB toolbox for automatic modulation classifier development
Automatic Modulation Classification implemented on different deep learning frameworks
Anomaly detection algorithm implementation in Python
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection with R
A collection of algorithms for anomaly detection
Anomaly detection using Autoencoder implemented with Keras 2.
Parallels solutions for antenna's placement problem.
Discover hidden patterns and relationships in unstructured data with Python
Code for The Assistive Multi-Armed Bandit (2019)
A multimodal approach on emotion recognition using audio and text.
GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in COVID-19 Classification
Official Code: Implicit 3D Orientation Learning for 6D Object Detection from RGB Images
Implementation of Semantic Hashing. Modified from Ruslan Salakhutdinov and Geoff Hinton's code of training Deep AutoEncoder
Reducing the Dimensionality of Data with Neural Network
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/
Replication of "Auto-encoder Based Data Clustering" Song et al
Using Keras to validate the simulation results according to Paper : "An Introduction to Deep Learning for the Physical Layer"
This shows how to use Autoencoders for learning constellations and receivers in fiber optical communications
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
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A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.