4 citations · 10 across the 8 of their papers we have counts for
6 papers · 1 filter
Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift
Mohammed Abdul Hafeez Khan, Parth Ganeriwala, Sarah M. Lehman +3
Lane detection models are often evaluated in a closed-world setting, where training and testing occur on the same dataset. We observe that, even within the same domain, cross-datas…
Runway vs. Taxiway: Challenges in Automated Line Identification and Notation Approaches
Parth Ganeriwala, Amy Alvarez, Abdullah AlQahtani +3
The increasing complexity of autonomous systems has amplified the need for accurate and reliable labeling of runway and taxiway markings to ensure operational safety. Precise detec…
Exploring Machine Learning Engineering for Object Detection and Tracking by Unmanned Aerial Vehicle (UAV)
Aneesha Guna, Parth Ganeriwala, Siddhartha Bhattacharyya
With the advancement of deep learning methods it is imperative that autonomous systems will increasingly become intelligent with the inclusion of advanced machine learning algorith…
Cross Dataset Analysis and Network Architecture Repair for Autonomous Car Lane Detection
Parth Ganeriwala, Siddhartha Bhattacharyya, Raja Muthalagu
Transfer Learning has become one of the standard methods to solve problems to overcome the isolated learning paradigm by utilizing knowledge acquired for one task to solve another…
AssistTaxi: A Comprehensive Dataset for Taxiway Analysis and Autonomous Operations
Parth Ganeriwala, Siddhartha Bhattacharyya, Sean Gunther +4
The availability of high-quality datasets play a crucial role in advancing research and development especially, for safety critical and autonomous systems. In this paper, we presen…
ALINA: Advanced Line Identification and Notation Algorithm
Mohammed Abdul Hafeez Khan, Parth Ganeriwala, Siddhartha Bhattacharyya +2
Labels are the cornerstone of supervised machine learning algorithms. Most visual recognition methods are fully supervised, using bounding boxes or pixel-wise segmentations for obj…