C&EN

A Machine Learning-Assisted Liquid Crystal Droplet Array Platform for the Sensitive and Selective Detection of Per- and Polyfluoroalkyl Substances (PFAS) in Water

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. You are free to share(copy and redistribute) this ...
IEEE

Conv4Rec: A 1-by-1 Convolutional Autoencoder for User Profiling Through Joint Analysis of Implicit and Explicit Feedback

Abstract: We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility ...
Frontiers

Multi-pollutant air quality forecasting using bidirectional attention and multi-scale temporal networks

1 Department of Electrical Engineering, Universiti Malaya, Kuala Lumpur, Malaysia 2 Faculty of Engineering and Information Technology, Southern University College, Skudai, Malaysia Introduction: ...
GitHub

Self-Learning-VAE-for-EEG-Artifact-Removal

This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...
C&EN

Explainable Deep Learning Framework for SERS Bioquantification

Melville Laboratory for Polymer Synthesis, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Rd, Cambridge CB2 1EW, U.K. Melville Laboratory for Polymer Synthesis, Yusuf Hamied ...
Scientific Research Publishing

Ghosal, I., Sarkar, S.S. and El Hallaoui, I. (2020) Lung Nodule Classification Using Convolutional Autoencoder and Clustering Augmented Learning Method (CALM). HSDM@ WSDM, 8.

TITLE: Optimizing Lung Cancer Detection in CT Imaging: A Wavelet Multi-Layer Perceptron (WMLP) Approach Enhanced by Dragonfly Algorithm (DA) ...
GitHub

autoencoder-mnist

Image Denoising with Autoencoders in R (University Project) Built a convolutional autoencoder in R using Keras/TensorFlow to perform image denoising on MNIST and CIFAR-10 datasets with varying levels ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...