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Found 5 papers, 0 papers with code
From Interpretable Filters to Predictions of Convolutional Neural Networks with Explainable Artificial Intelligence
Explanation results obtained from the LIME, SmoothGrad, and Grad-CAM highlight important features of different spectrograms and their relevance to classification.
Ensemble Consensus-based Representation Deep Reinforcement Learning for Hybrid FSO/RF Communication Systems
To overcome this, we lift this problem to ensemble consensus-based representation learning for deep reinforcement called DQNEnsemble-FSO/RF.
A Data Augmented Approach to Transfer Learning for Covid-19 Detection
In this work, we demonstrate that how we can augment limited X-ray images data by using Contrast limited adaptive histogram equalization (CLAHE) to train the last layer of the pre-trained deep learning models to mitigate the bias of transfer learning for Covid-19 detection.
Understanding Human Innate Immune System Dependencies using Graph Neural Networks
The development of this vaccine is time-consuming and requires a deep understanding of the innate immune response system.
Enterprise Analytics using Graph Database and Graph-based Deep Learning
Specifically, we have applied the graph convolution network (GCN) to enable CRM analytics to forecast sales.
