126 citations · 268 across the 8 of their papers we have counts for
9 papers
On Correlation of Features Extracted by Deep Neural Networks
Babajide O. Ayinde, Tamer Inanc, Jacek M. Zurada
Redundancy in deep neural network (DNN) models has always been one of their most intriguing and important properties. DNNs have been shown to overparameterize, or extract a lot of…
Diversity Regularized Adversarial Learning
Babajide O. Ayinde, Keishin Nishihama, Jacek M. Zurada
The two key players in Generative Adversarial Networks (GANs), the discriminator and generator, are usually parameterized as deep neural networks (DNNs). On many generative tasks,…
Optimal Placement of Relay Nodes in Wireless Sensor Network Using Artificial Bee Colony Algorithm
Hashim A. Hashim, B. O. Ayinde, M. A. Abido
Deploying sensor nodes randomly most of the time generates initial communication hole even in highly dense networks. These communication holes cannot be totally eliminated even whe…
Building Efficient ConvNets using Redundant Feature Pruning
Babajide O. Ayinde, Jacek M. Zurada
This paper presents an efficient technique to prune deep and/or wide convolutional neural network models by eliminating redundant features (or filters). Previous studies have shown…
Energy-efficient Deployment of Relay Nodes in Wireless Sensor Networks using Evolutionary Techniques
Babajide O. Ayinde, Hashim A. Hashim
Random deployment of sensor nodes is susceptible to initial communication hole, even when the network is densely populated. However, eliminating holes using structural deployment p…
Deep Learning of Nonnegativity-Constrained Autoencoders for Enhanced Understanding of Data
Babajide O. Ayinde, Jacek M. Zurada
Unsupervised feature extractors are known to perform an efficient and discriminative representation of data. Insight into the mappings they perform and human ability to understand…