4 citations · 5 across the 5 of their papers we have counts for
5 papers
Classification of developmental and brain disorders via graph convolutional aggregation
Ibrahim Salim, A. Ben Hamza
While graph convolution based methods have become the de-facto standard for graph representation learning, their applications to disease prediction tasks remain quite limited, part…
Learning to recognize occluded and small objects with partial inputs
Hasib Zunair, A. Ben Hamza
Recognizing multiple objects in an image is challenging due to occlusions, and becomes even more so when the objects are small. While promising, existing multi-label image recognit…
Spatio-temporal MLP-graph network for 3D human pose estimation
Tanvir Hassan, A. Ben Hamza
Graph convolutional networks and their variants have shown significant promise in 3D human pose estimation. Despite their success, most of these methods only consider spatial corre…
Iterative Graph Filtering Network for 3D Human Pose Estimation
Zaedul Islam, A. Ben Hamza
Graph convolutional networks (GCNs) have proven to be an effective approach for 3D human pose estimation. By naturally modeling the skeleton structure of the human body as a graph,…
A Graph Encoder-Decoder Network for Unsupervised Anomaly Detection
Mahsa Mesgaran, A. Ben Hamza
A key component of many graph neural networks (GNNs) is the pooling operation, which seeks to reduce the size of a graph while preserving important structural information. However,…