AiAge - Artificial Intelligence AGe

This tutorial discusses how to use the genetic algorithm (GA) for reducing the feature vector extracted from the Fruits360 dataset in Python mainly using NumPy and Sklearn. Feature Reduction using Genetic Algorithm with Python

This tutorial discusses how to use the genetic algorithm (GA) for reducing the feature vector extracted from the Fruits360 dataset in Python mainly using NumPy and Sklearn. Feature Reduction using Genetic Algorithm with Python

This tutorial explains the usage of the genetic algorithm for optimizing the network weights of an Artificial Neural Network for improved performance. Artificial Neural Networks Optimization using Genetic Algorithm with Python

Artificial Neural Networks Optimization using Genetic Algorithm with Python - Towards Data Science In a previous tutorial titled “ Artificial Neural Network Implementation using NumPy and Classification of the Fruits360 Image Dataset ” available in my LinkedIn profile at this  link , an artificial neural network (ANN) is created for classifying 4 classes of the Fruits360 image dataset. The source code used in this tutorial is available in my  GitHub page . This tutorial is also available at TowardsDataScience  here . A quick summary of this tutorial is extracting the feature vector (360 bins hue channel histogram) and reducing it to just 102 element by using a filter-based technique using the standard deviation. Later, the ANN is built from scratch using NumPy. The ANN was not completely created as just the forward pass was made ready but there is no backward pass for updating the network weights. This is why the accuracy is very low and not exceeds 4...

This tutorial builds artificial neural network in Python using NumPy from scratch in order to do an image classification application for the Fruits360 dataset Artificial Neural Network Implementation using NumPy and Image Classification

Building Surveillance System Using USB Camera and Wireless-Connected Raspberry Pi

Building an Image Classifier Running on Raspberry Pi

Derivation of Convolutional Neural Network from Fully Connected Network Step-By-Step In image analysis, #convolutional neural networks (#CNNs or #ConvNets for short) are time and memory efficient than fully connected (#FC) networks. But why? What are the advantages of ConvNets over FC networks in image analysis? How is #ConvNet derived from FC networks? Where the term #convolution in CNNs came from? These questions are to be answered in this #article. #FullyConnected #CNN #DeepLearning #DL #MachineLearning #ML #ANN #NeuralNetwork #NN #DataAnalysis #DataScience #KDnuggets Article @ #LinkedIn https://www.linkedin.com/pulse/derivation-convolutional-neural-network-from-fully-connected-gad/ Article @ #SlideShare https://www.slideshare.net/AhmedGadFCIT/derivation-of-convolutional-neural-network-convnet-from-fully-connected-network

Are New Technologies Killing Their Ancestors?