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20212024
most citedAI Driven Road Maintenance Inspection

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2024

Beyond Unimodal Learning: The Importance of Integrating Multiple Modalities for Lifelong Learning

Fahad Sarfraz, Bahram Zonooz, Elahe Arani

While humans excel at continual learning (CL), deep neural networks (DNNs) exhibit catastrophic forgetting. A salient feature of the brain that allows effective CL is that it utili…

cs.CV2022

AI-Driven Road Maintenance Inspection v2: Reducing Data Dependency & Quantifying Road Damage

Haris Iqbal, Hemang Chawla, Arnav Varma +4

Road infrastructure maintenance inspection is typically a labor-intensive and critical task to ensure the safety of all road users. Existing state-of-the-art techniques in Artifici…

cs.CV2022

A Comprehensive Study of Vision Transformers on Dense Prediction Tasks

Kishaan Jeeveswaran, Senthilkumar Kathiresan, Arnav Varma +3

Convolutional Neural Networks (CNNs), architectures consisting of convolutional layers, have been the standard choice in vision tasks. Recent studies have shown that Vision Transfo…

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…