12 citations · 12 across the 1 of their papers we have counts for
6 papers
HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data
Abduallah Mohamed, Fernando Lejarza, Stephanie Cahail +2
The problem of human activity recognition from mobile sensor data applies to multiple domains, such as health monitoring, personal fitness, daily life logging, and senior care. A c…
Inner Ensemble Networks: Average Ensemble as an Effective Regularizer
Abduallah Mohamed, Muhammed Mohaimin Sadiq, Ehab AlBadawy +2
We introduce Inner Ensemble Networks (IENs) which reduce the variance within the neural network itself without an increase in the model complexity. IENs utilize ensemble parameters…
Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction
Abduallah Mohamed, Kun Qian, Mohamed Elhoseiny +1
Better machine understanding of pedestrian behaviors enables faster progress in modeling interactions between agents such as autonomous vehicles and humans. Pedestrian trajectories…
Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development
Kun Qian, Abduallah Mohamed, Christian Claudel
Flash floods in urban areas occur with increasing frequency. Detecting these floods would greatlyhelp alleviate human and economic losses. However, current flood prediction methods…
IEA: Inner Ensemble Average within a convolutional neural network
Abduallah Mohamed, Xinrui Hua, Xianda Zhou +1
Ensemble learning is a method of combining multiple trained models to improve model accuracy. We propose the usage of such methods, specifically ensemble average, inside Convolutio…
MCRM: Mother Compact Recurrent Memory
Abduallah A. Mohamed, Christian Claudel
LSTMs and GRUs are the most common recurrent neural network architectures used to solve temporal sequence problems. The two architectures have differing data flows dealing with a c…