6 citations · 15 across the 9 of their papers we have counts for
9 papers
Spatiotemporal Multi-Task Graph Transformer for Trip-Level Transit Prediction
Oluwaleke Yusuf, Adil Rasheed, Frank Lindseth
Passenger count data from public transit systems reveals urban mobility patterns and is essential for planning, operation, and optimisation. However, non-linear spatiotemporal inte…
Estimation of Segmental Longitudinal Strain in Transesophageal Echocardiography by Deep Learning
Anders Austlid Taskén, Thierry Judge, Erik Andreas Rye Berg +8
Segmental longitudinal strain (SLS) of the left ventricle (LV) is an important prognostic indicator for evaluating regional LV dysfunction, in particular for diagnosing and managin…
Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving
Florian Wintel, Sigmund H. Høeg, Gabriel Kiss +1
End-to-end planning systems for autonomous driving are rapidly improving, especially in closed-loop simulation environments like CARLA. Many such driving systems either do not cons…
SegDesicNet: Lightweight Semantic Segmentation in Remote Sensing with Geo-Coordinate Embeddings for Domain Adaptation
Sachin Verma, Frank Lindseth, Gabriel Kiss
Semantic segmentation is essential for analyzing highdefinition remote sensing images (HRSIs) because it allows the precise classification of objects and regions at the pixel level…
Deep HM-SORT: Enhancing Multi-Object Tracking in Sports with Deep Features, Harmonic Mean, and Expansion IOU
Matias Gran-Henriksen, Hans Andreas Lindgaard, Gabriel Kiss +1
This paper introduces Deep HM-SORT, a novel online multi-object tracking algorithm specifically designed to enhance the tracking of athletes in sports scenarios. Traditional multi-…
Exploring Urban Mobility Trends using Cellular Network Data
Oluwaleke Yusuf, Adil Rasheed, Frank Lindseth
The growth of urban areas intensifies the need for sustainable, efficient transportation infrastructure and mobility systems, driving initiatives to enhance infrastructure and publ…
Unveiling Urban Mobility Patterns: A Data-Driven Analysis of Public Transit
Oluwaleke Yusuf, Adil Rasheed, Frank Lindseth
The expansion of urban centers necessitates enhanced efficiency and sustainability in their transportation infrastructure and mobility systems. The big data obtainable from various…
Geo-locating Road Objects using Inverse Haversine Formula with NVIDIA Driveworks
Mamoona Birkhez Shami, Gabriel Kiss, Trond Arve Haakonsen +1
Geolocation is integral to the seamless functioning of autonomous vehicles and advanced traffic monitoring infrastructures. This paper introduces a methodology to geolocate road ob…
Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation
Javier Pérez de Frutos, André Pedersen, Egidijus Pelanis +5
Purpose: This study aims to explore training strategies to improve convolutional neural network-based image-to-image deformable registration for abdominal imaging. Methods: Differe…