The final classification is executed using a Back Propagation Neural Network Classifier. The efficacy of our model was tested using images of barley afflicted with the specified diseases. The results ...

Objective: A neurodegenerative disease (NDD) detection algorithm using a convolutional neural network (CNN) and wavelet coherence spectrogram of gait synchronization was developed to classify NDD ...

Deep learning (DL) techniques, more specifically Convolutional Neural Networks (CNNs), have become increasingly popular in advancing the field of data science and have had great successes in a wide ...

Neural networks are more powerful than these alternatives, in both the mathematical sense and ordinary language sense, but neural networks are more complex than the alternatives. Let me reiterate that ...

Keywords: robot image classification, CapsNet neural network, MobileNetV2, attention module, spatial and channel information. Citation: Zhang J, Yu X, Lei X and Wu C (2022) A novel CapsNet neural ...

This repository provides an overview of various deep learning algorithms for image classification, focusing on their structures, use cases, and implementation in Python using TensorFlow/Keras. The ...

Using a convolution neural network algorithm, this automated external defibrillator device enters the challenging field to improve bystander defibrillation, the detection of a shockable rhythm, and to ...