IEEE19d
Inverse Design of FBG-Based Optical Filters Using Deep Learning: A Hybrid CNN-MLP Approach
We utilized a convolutional neural network (CNN) to derive an apodization profile that facilitates the design of a narrow, dual-channel filter with identical channels, each featuring a 0.75 nm ...
Frontiers25d
Investigation of a transformer-based hybrid artificial neural networks for climate data prediction and analysis
Methods: In light of this, this paper proposes a hybrid deep learning model based on Transformer-Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) to improve the accuracy of climate ...
IEEE29d
MCTGCL: Mixed CNN–Transformer for Mars Hyperspectral Image Classification With Graph Contrastive Learning
To address these challenges, we propose a mixed CNN-transformer network for Mars HSI classification with graph contrastive learning to enhance classification performance. Specifically, we introduce an ...
Frontiers1mon
Evaluation of machine learning techniques for real-time prediction of implanted lower limb mechanics
Several predictive algorithms were explored, including linear regression (LRM), multilayer perceptron (MLP), bi-directional long short-term memory (biLSTM), convolutional neural network (CNN), and ...
Yahoo Finance10mon
Recurrent MLP & Infrastructure Class I (RMLPX)
The Magnificent Seven tech stocks and big AI players drove double-digit gains at many large-cap mutual funds. The top fund returned 51.8%. On the latest installment of Good Buy or Goodbye ...