IEEE

Convolutional Neural Networks for Direction of Arrival Estimation Compared to Classical ...

Abstract: Recently, there has been a proliferation of applied machine learning (ML) research, including the use of convolutional neural networks (CNNs) for direction of arrival (DoA) estimation. With ...
IEEE

Convolutional Neural Network Image Classification Based on Different Color Spaces

Abstract: Although Convolutional Neural Networks (CNNs) have achieved remarkable success in image classification, most CNNs use image datasets in the Red-Green-Blue (RGB) color space (one of the most ...
Scientific Research Publishing

Prediction of the Price of Advanced Global Stock Markets Using Machine Learning ...

Finance and Business Sector, Institute of Public Administration, Riyadh, Saudi Arabia. This paper seeks to forecast the daily closing prices of advanced global stock markets by employing machine ...
Frontiers

Convolutional long short-term memory neural network for groundwater change prediction

Forecasting groundwater changes is a crucial step towards effective water resource planning and sustainable management. Conventional models still demonstrated insufficient performance when aquifers ...
Frontiers

PNNGS, a multi-convolutional parallel neural network for genomic selection

Genomic selection (GS) can accomplish breeding faster than phenotypic selection. Improving prediction accuracy is the key to promoting GS. To improve the GS prediction accuracy and stability, we ...
GitHub

CIFAR-10 IMAGE CLASSIFICATION WITH KERAS CONVOLUTIONAL NEURAL NETWORK TUTORIAL

Keras is compatible with Python 2.7-3.5"[1]. Since Semptember 2016, Keras is the second-fastest growing Deep Learning framework after Google's Tensorflow, and the third largest after Tensorflow and ...