Picture for Adedotun Akintayo

Adedotun Akintayo

3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems

Add code
Jan 06, 2021
Figure 1 for 3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems
Figure 2 for 3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems
Figure 3 for 3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems
Figure 4 for 3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems
Viaarxiv icon

Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data

Add code
Feb 06, 2017
Figure 1 for Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data
Figure 2 for Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data
Figure 3 for Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data
Figure 4 for Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data
Viaarxiv icon

Energy Prediction using Spatiotemporal Pattern Networks

Add code
Feb 03, 2017
Figure 1 for Energy Prediction using Spatiotemporal Pattern Networks
Figure 2 for Energy Prediction using Spatiotemporal Pattern Networks
Figure 3 for Energy Prediction using Spatiotemporal Pattern Networks
Figure 4 for Energy Prediction using Spatiotemporal Pattern Networks
Viaarxiv icon

A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge

Add code
Aug 17, 2016
Figure 1 for A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge
Figure 2 for A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge
Figure 3 for A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge
Figure 4 for A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge
Viaarxiv icon

LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement

Add code
Apr 15, 2016
Figure 1 for LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement
Figure 2 for LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement
Figure 3 for LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement
Figure 4 for LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement
Viaarxiv icon

Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hi-speed Flame Video

Add code
Mar 25, 2016
Figure 1 for Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hi-speed Flame Video
Figure 2 for Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hi-speed Flame Video
Figure 3 for Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hi-speed Flame Video
Figure 4 for Early Detection of Combustion Instabilities using Deep Convolutional Selective Autoencoders on Hi-speed Flame Video
Viaarxiv icon

An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection

Add code
Mar 25, 2016
Figure 1 for An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection
Figure 2 for An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection
Figure 3 for An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection
Figure 4 for An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection
Viaarxiv icon