Click here to Skip to main content
65,938 articles
CodeProject is changing. Read more.
Everything / artificial-intelligence / neural-network

Neural Network

neural-network

Great Reads

by Gary.Miller.WPF
MNIST Digit recognition in C#
by Dr. Song Li
This is a library to implement Neural Networks in JavaScript.
by Mahsa Hassankashi
This article also has a practical example for the neural network. You read here what exactly happens in the human brain, while you review the artificial neuron network.
by Thomas Daniels
This article describes the making of a tic tac toe player that uses neural networks and machine learning.

Latest Articles

by Gary.Miller.WPF
MNIST Digit recognition in C#
by Dr. Song Li
This is a library to implement Neural Networks in JavaScript.
by Mahsa Hassankashi
This article also has a practical example for the neural network. You read here what exactly happens in the human brain, while you review the artificial neuron network.
by Thomas Daniels
This article describes the making of a tic tac toe player that uses neural networks and machine learning.

All Articles

Sort by Score

neural-network 

by Gary.Miller.WPF
MNIST Digit recognition in C#
by Dr. Song Li
This is a library to implement Neural Networks in JavaScript.
by Mahsa Hassankashi
This article also has a practical example for the neural network. You read here what exactly happens in the human brain, while you review the artificial neuron network.
by Thomas Daniels
This article describes the making of a tic tac toe player that uses neural networks and machine learning.
by Sergey L. Gladkiy
In this article we’ll build the network we’ve designed using the Keras framework.
by Sergey L. Gladkiy
In this article we’ll guide you through one of the most difficult steps in the DL pipeline: the CNN design.
by Sergey L. Gladkiy
In this article we train the CNN for age estimation.
by Sergey L. Gladkiy
In this article we will explain how to use the pre-trained CNN for estimating a person’s age from an image.
by Sergio Virahonda
In this article we talk about anomaly detection on time series data.
by Raphael Mun
In this article we will create a knowledge chatbot.
by Sergio Virahonda
In this article we’ll combine forecasting and detection on a live stream of Bitcoin price data.
by Sergio Virahonda
In the next article, we are going to discuss forecasting on Bitcoin time series.
by Jarek Szczegielniak
Having converted a ResNet model to the Core ML format in the previous article, in this article we’ll now use it in a simple iOS application.
by MehreenTahir
In this article, we will train a deep learning model to detect and count the number of people in a given area.
by MehreenTahir
This is the first in an article series where we’re going to show how to make an AI queue length detector.
by MehreenTahir
In this article, we’ll explore some other algorithms used for object detection and will learn to implement them for custom object detection.
by hemanthk119
Genetic Mutations of Neural Networks to produce better offspring in fish like virtual creatures
by Joel Ivory Johnson
Image classification using Arm NN on Android mobile devices
by Joel Ivory Johnson
In this article we will consider the ways in which the network could be further optimized.
by Andrew Kirillov
The article demonstrates usage of ANNT library for creating fully connected ANNs and applying them to different tasks.
by Andrew Kirillov
Use of ANNT library to create recurrent ANNs and apply them to different tasks
by Hatem Mostafa
Artificial Neural Network C++ class with two use cases: Counter and Handwritten Digits recognition
by Dawid Borycki
In this article, we'll demonstrate building an Arm NN-based application for an IoT device that can perform automatic trash sorting through image analysis.
by Bhairav Thakkar
A basic artificial neural network code for experimenting
by Emiliano Musso
Basics of implementing a neural network in VB.NET
by Gamil Yassin
Perceptron, when to use it and sample code
by Gamil Yassin
Part 4 of a series of articles demonstrating .NET AI library from scratch
by Gamil Yassin
Types of Artificial Neural Networks
by Jarek Szczegielniak
In this article we’ll create a Core ML pipeline to be our end-to-end model.
by Abdulkader Helwan
In this article, we implement a CycleGAN from scratch.
by Abdulkader Helwan
In this article, we implement a CycleGAN with a residual-based generator.
by Jarek Szczegielniak
In this article we can proceed to train our custom hot dog detection model using Apple’s Create ML.
by Jarek Szczegielniak
In this last article in this series, we’ll extend the application to use our YOLO v2 model for object detection.
by philoxenic
In this article, you will be up and running, and will have done your first piece of reinforcement learning.
by philoxenic
In this article, we will see what’s going on behind the scenes and what options are available for changing the reinforcement learning.
by Ryan Peden
A code-first introduction to neural networks
by Philipp_Engelmann
Competing on kaggle.com for the first time
by Jarek Szczegielniak
In this series, we’ll use a pretrained model to create an iOS application that will detect multiple persons and objects in a live camera feed rather than in a static picture.
by Jarek Szczegielniak
In this article we'll convert a ResNet model to the Core ML format.
by Dawid Borycki
How to choose and convert an existing TensorFlow model to work with Arm NN and best practices for model conversion and implementing Arm NN solutions.
by Philipp_Engelmann
In this series, I want to show you how to create a simple console-based Turing machine in Python. You can check out the full source code on https://github.com/phillikus/turing_machine. In this part, I will explain the fundamental theory behind Turing machines and set up the project based on that.
by Philipp_Engelmann
How to create a Turing machine in Python - Part 2
by Jarek Szczegielniak
In this article we are ready to include detection decoding directly in the Core ML model.
by Joel Ivory Johnson
In this article we will create an Android application and import our TensorFlow Lite model into it.
by Harinder Saluja
Implement Neural Network in SQL Server
by Jarek Szczegielniak
In this article, we will decode the Core ML YOLO Model by transforming an array of abstract numbers to a human-readable form.
by Jarek Szczegielniak
In the next article, we’ll do the same but with array operations. This will allow us to include the decoding logic directly in the model.
by Arnaldo P. Castaño
In this article, we will examine a convolutional neural network for the problem of coin recognition, and we will implement one in Keras.NET.
by Arnaldo P. Castaño
In this article we will examine the CNN we implemented for coin recognition using Keras.NET.
by Arnaldo P. Castaño
To end off this series, we will present the alternative of adapting a pre-trained CNN to the coin recognition problem we have been examining all along.
by Arnaldo P. Castaño
In this article we will go over the basics of supervised machine learning and what the training and verification phases consist of.
by Sergey L. Gladkiy
In the next article, we’ll use a pre-trained DNN to detect pests on video.
by Sergey L. Gladkiy
In this article, we’ll show you how to develop a simple motion detector and combine it with the trained DNN model to detect moose on video.
by Sergey L. Gladkiy
In this we’ll talk about some ideas for detecting "exotic" pests, such as moose and armadillos.
by Sergey L. Gladkiy
In this article, we’ll test our detection algorithm on a Raspberry Pi 3 device and create the "scare pests away" part of our pest eliminator by playing a loud sound.
by Sergey L. Gladkiy
In this article, we’ll see how the same result can be achieved by data augmentation.
by Abdulkader Helwan
In this article we show you how to train VGG19 to recognize what people are wearing.
by Miguel Diaz Kusztrich
Using R to explore complexity of time series generated by simple process
by Abdulkader Helwan
In this article we show you how to build a Generative Adversarial Network (GAN) for fashion design generation.
by Raphael Mun
In this article, I will show you how quickly and easily set up and use TensorFlow.js to train a neural network to make predictions from data points.
by KristianEkman
A C# object oriented Neural Network, trainer, and Windows Forms user interface for recognitions of hand-written digits.
by Sergey L. Gladkiy
In this article, we’ll discuss some aspects of developing a facial recognition system from scratch.
by hemanthk119
Image Classification implementation using Deep Belief Networks and Convolutional Neural Networks in .NET
by Huseyin Atasoy
An image classifier / tagger based on convolutional neural networks. Now more than 10 times faster with the Intel MKL support.
by Nikola M. Živković
Implementation of Convolutional Neural Network using Python and Keras
by Bahrudin Hrnjica
How to implement data normalization as regular neural network layer, which can simply training process and data preparation
by Thomas Daniels
In this article, let’s dive into Keras, a high-level library for neural networks.
by philoxenic
In this article, we start to look at the OpenAI Gym environment and the Atari game Breakout.
by Jarek Szczegielniak
In the next article, we’ll start working on the iOS application that will use that model.
by philoxenic
In this article we will learn from the contents of the game’s RAM instead of the pixels.
by philoxenic
In this article, we will see how we can improve by approaching the RAM in a slightly different way.
by philoxenic
In this article, we will see how you can use a different learning algorithm (plus more cores and a GPU) to train much faster on the mountain car environment.
by philoxenic
In this final article in this series, we will look at slightly more advanced topics: minimizing the "jitter" of our Breakout-playing agent, as well as performing grid searches for hyperparameters.
by Alibaba Cloud
In this post, we learn about algorithms that help implement ML functions.
by Ammar Albush 1997
Logo Recognition System Program written in C# .NET 6.0 Windows Form (Tensorflow.net,Tensorflow.keras,Emgu Cv,ScottPlot.WinForms,Newtonsoft.Json)
by Vietdungiitb
The research focuses on the presentation of word recognition technique for an online handwriting recognition system which uses multiple component neural networks (MCNN) as the exchangeable parts of the classifier.
by mohammad farahi
English Number recognition with Multi Layer Perceptron Neural Network (MLP)
by Abdulkader Helwan
In this article we’ll show you how to use transfer learning to fine-tune the VGG19 model to classify fashion clothing categories.
by Jarek Szczegielniak
In this article we’ll start data preparation for this new, custom model, to be later trained using the Create ML framework.
by Sergey L. Gladkiy
In this article we’ll create the training dataset for our pest of choice: The moose.
by Sergio Virahonda
In this article, we learn how to prepare time series data to be fed to machine learning (ML) and deep learning (DL) models.
by Sergey L. Gladkiy
In this article, we’ll modify the code for real-time processing on an edge device.
by Sergey L. Gladkiy
In this article, we’ll showcase the Python code for launching these models and detect humans in images.
by Sergey L. Gladkiy
This is the first in an article series where we’ll show you how to detect people in real time (or near-real time) on Raspberry Pi.
by Sergey L. Gladkiy
In this article, we’ll see how you can install Python-OpenCV on the device and run the code.
by Sergey L. Gladkiy
In this article, we’ll test the accuracy and the performance of the MibileNet and SqueezeNet models on the Raspberry Pi device.
by Sergey L. Gladkiy
In this article, we compared two DNN types we can use to detect pests: detectors and classifiers.
by Intel
Improve Performance on Multicore and Many-Core Intel® Architectures, Particularly for Deep Neural Networks
by Byte-Master-101
Neural Networks can do a lot of amazing things, and you can understand how you can make one from the ground up. You can actually be surprised how easy it is to develop one from scratch!
by Byte-Master-101
In Part 2, the Neural Network made in Part 1 is tested in an environment made in Unity so that we can see how well it performs.
by Byte-Master-101
Now that we got the basics over with, it's time for improvement!
by Abdulkader Helwan
In this article we evaluate VGG19 using real images taken by a phone camera.
by Joel Ivory Johnson
This is the first in a series of articles on using TensorFlow Lite on Android to bring the power of machine learning and deep neural networks to mobile application
by Jarek Szczegielniak
In this article we prepare our development environment.
by R. Stacy Smyth
Approach I used to get the CNN to behave in a more intuitively sensible way
by Serge Desmedt
A try it yourself guide to the basic math behind perceptrons
by Serge Desmedt
A try it yourself guide to the basic math behind ADALINE perceptron
by Sergey L. Gladkiy
In this article, we’ll discuss training our DNN classifier with the augmented dataset.
by Abdulkader Helwan
In this article, we train a CycleGAN with a U-Net-based generator.
by Abdulkader Helwan
In this article we show you how to train the GAN for fashion design generation.
by Joel Ivory Johnson
In this article we will generate output from a program will provide a TensorFlow freeze graph ready to be used or converted to TensorFlow Lite.
by Joel Ivory Johnson
In this article we will take a pre-trained neural network and adapt it for use in TensorFlow Lite.
by Abdulkader Helwan
In this article, we discuss the CycleGAN architecture.
by Keith Pijanowski
In this article, I provided a brief overview of the ONNX Runtime and the ONNX format.
by Keith Pijanowski
In this article, I provided a brief overview of the ONNX Runtime and the ONNX format.
by Joel Ivory Johnson
In the previous installation of this series, a TensorFlow Lite interpreter had examined an image and produced its output. In this article we learn how to interpret these results and create visualizations for them.