Binary star population of open cluster NGC 2158 explored with Hubble

Astronomers have analyzed the images collected by the Hubble Space Telescope (HST) to investigate a galactic open cluster ...
psypost.org

Severe sleep problems is associated with fewer years of healthy brain function

A new analysis of data from older Americans indicates that chronic sleep disturbances are associated with a shorter lifespan and fewer years spent with a healthy brain. The research suggests that ...
IEEE

FPGA Implementation of Sigmoid, Hyperbolic Tangent and Softmax Functions using Efficient Architecture for Exponential Function

Abstract: Machine learning (ML) algorithms take help of different activation functions to calculate probabilities for classification problem. Over the past few years researchers are trying to ...
Scientific Research Publishing

Pedamonti, D. (2018) Comparison of Non-Linear Activation Functions for Deep Neural Networks on MNIST Classification Task. arXiv.

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 ...
Hosted on MSN

20 Activation Functions in Python for Deep Neural Networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python Tropical Storm ...
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 ...
GitHub

Binary Classification Issue #1647

i am running binary classification report. my "target" column is binary 0,1 values, "pred_lablel" is binary 01, values and "prediction" is probabilities between 0-1 i get auc/roc, log loss but ...
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...