134 citations · 295 across the 6 of their papers we have counts for
6 papers
MaskConnect: Connectivity Learning by Gradient Descent
Karim Ahmed, Lorenzo Torresani
Although deep networks have recently emerged as the model of choice for many computer vision problems, in order to yield good results they often require time-consuming architecture…
Weighted Transformer Network for Machine Translation
Karim Ahmed, Nitish Shirish Keskar, Richard Socher
State-of-the-art results on neural machine translation often use attentional sequence-to-sequence models with some form of convolution or recursion. Vaswani et al. (2017) propose a…
Connectivity Learning in Multi-Branch Networks
Karim Ahmed, Lorenzo Torresani
While much of the work in the design of convolutional networks over the last five years has revolved around the empirical investigation of the importance of depth, filter sizes, an…
BranchConnect: Large-Scale Visual Recognition with Learned Branch Connections
Karim Ahmed, Lorenzo Torresani
We introduce an architecture for large-scale image categorization that enables the end-to-end learning of separate visual features for the different classes to distinguish. The pro…
Network of Experts for Large-Scale Image Categorization
Karim Ahmed, Mohammad Haris Baig, Lorenzo Torresani
We present a tree-structured network architecture for large scale image classification. The trunk of the network contains convolutional layers optimized over all classes. At a give…
VSCAN: An Enhanced Video Summarization using Density-based Spatial Clustering
Karim M. Mohamed, Mohamed A. Ismail, Nagia M. Ghanem
In this paper, we present VSCAN, a novel approach for generating static video summaries. This approach is based on a modified DBSCAN clustering algorithm to summarize the video con…