WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
IEEE

A DNA-Level Convolutional Neural Network Based on Strand Displacement Reaction for Image Recognition

Abstract: Over the past few decades, convolutional neural network (CNN) has found broad applications in image recognition. Nevertheless, the operational environment of CNN is facing significant ...
Hosted on MSN

Activation functions in neural networks: Types and examples

In this video, we will see What is Activation Function in Neural network, types of Activation function in Neural Network, why to use an Activation Function and which Activation function to use. The ...
Hosted on MSN

Neural network activation functions explained simply

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! #NeuralNetworks ...
Scientific Research Publishing

Mostafanejad, M. (2023) Unification of Popular Artificial Neural Network Activation Functions. arXiv:2302.11007.

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Ars Technica

Neural network finds an enzyme that can break down polyurethane

You’ll often hear plastic pollution referred to as a problem. But the reality is that it’s multiple problems. Depending on the properties we need, we form plastics out of different polymers, each of ...
Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
IEEE

Skew Logistic Distribution Applied as Activation Function in Artificial Neural Networks

Abstract: In recent years, Artificial Neural Networks (ANNs) have stood out among machine learning algorithms in many applications, such as image and video pattern recognition. Activation functions ...