activity
20192024
most citedLearning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System

37 citations · 64 across the 29 of their papers we have counts for

collaborators
Showing 2021Show all

7 papers · 1 filter

cs.CV2021

Does Thermal data make the detection systems more reliable?

Shruthi Gowda, Bahram Zonooz, Elahe Arani

Deep learning-based detection networks have made remarkable progress in autonomous driving systems (ADS). ADS should have reliable performance across a variety of ambient lighting…

cs.LG2021

Improving the Efficiency of Transformers for Resource-Constrained Devices

Hamid Tabani, Ajay Balasubramaniam, Shabbir Marzban +2

Transformers provide promising accuracy and have become popular and used in various domains such as natural language processing and computer vision. However, due to their massive n…

cs.CV2021

Highlighting the Importance of Reducing Research Bias and Carbon Emissions in CNNs

Ahmed Badar, Arnav Varma, Adrian Staniec +5

Convolutional neural networks (CNNs) have become commonplace in addressing major challenges in computer vision. Researchers are not only coming up with new CNN architectures but ar…

cs.CV20211 cited

AI Driven Road Maintenance Inspection

Ratnajit Mukherjee, Haris Iqbal, Shabbir Marzban +5

Road infrastructure maintenance inspection is typically a labour-intensive and critical task to ensure the safety of all the road users. In this work, we propose a detailed methodo…

cs.LG2021

Challenges and Obstacles Towards Deploying Deep Learning Models on Mobile Devices

Hamid Tabani, Ajay Balasubramaniam, Elahe Arani +1

From computer vision and speech recognition to forecasting trajectories in autonomous vehicles, deep learning approaches are at the forefront of so many domains. Deep learning mode…

cs.CV2021

Perceptual Loss for Robust Unsupervised Homography Estimation

Daniel Koguciuk, Elahe Arani, Bahram Zonooz

Homography estimation is often an indispensable step in many computer vision tasks. The existing approaches, however, are not robust to illumination and/or larger viewpoint changes…