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 ...

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!

1 School of Electronics and Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou, China 2 Department of Mechanical and Electrical Engineering, Henan Vocational College of ...

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 ...

Organizations that track the material are reporting a surge in A.I. images and videos, which are threatening to overwhelm law enforcement. By Cecilia Kang Cecilia Kang has covered child online safety ...

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 ...