Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Abstract: Deep learning-based approaches to hyperspectral image analysis have attracted large attention and exhibited high performance in image classification tasks. However, deployment of deep ...

Deepfakes of Venezuela’s ousted president, Nicolás Maduro, flooded the internet after his capture, in a new collision of breaking news and artificial intelligence. By Stuart A. Thompson and Tiffany ...

90% accuracy resnet-like CNN from scratch for Intel Image Classification dataset WITHOUT transfer learning and with complex metrics.

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Using single-scale feature maps for classification training, the network generates large prediction regions and cannot adequately characterize image details. Therefore, the multi-scale feature fusion ...

This project demonstrates image classification using Convolutional Neural Networks (CNNs) in Python with TensorFlow and Keras, trained and tested on the CIFAR-10 dataset. The CIFAR-10 dataset consists ...

Classifying corn varieties presents a significant challenge due to the high-dimensional characteristics of hyperspectral images and the complexity of feature extraction, which hinder progress in ...