David Hagerman

According to our database, David Hagerman authored at least 9 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

ARTA: Adaptive Mixed-Resolution Token Allocation for Efficient Dense Feature Extraction.

David Hagerman, Roman Naeem, Erik Brorsson, Fredrik Kahl, Lennart Svensson

CoRR, March, 2026

2025

RefTr: Recurrent Refinement of Confluent Trajectories for 3D Vascular Tree Centerline Graphs.

Roman Naeem, David Hagerman, Jennifer Alvén, Fredrik Kahl

CoRR, November, 2025

Trexplorer Super: Topologically Correct Centerline Tree Tracking of Tubular Objects in CT Volumes.

Roman Naeem, David Hagerman, Jennifer Alvén, Lennart Svensson, Fredrik Kahl

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

Optimizing Gene-Based Testing for Antibiotic Resistance Prediction.

David Hagerman, Anna Johnning, Roman Naeem, Fredrik Kahl, Erik Kristiansson, Lennart Svensson

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Trexplorer: Recurrent DETR for Topologically Correct Tree Centerline Tracking.

Roman Naeem, David Hagerman, Lennart Svensson, Fredrik Kahl

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

SwInception - Local Attention Meets Convolutions.

David Hagerman, Roman Naeem, Jakob Lindqvist, Carl Lindström, Fredrik Kahl, Lennart Svensson

Proceedings of the Pattern Recognition and Artificial Intelligence, 2024

2023

Masked Autoencoder for Self-Supervised Pre-training on Lidar Point Clouds.

Georg Hess, Johan Jaxing, Elias Svensson, David Hagerman, Christoffer Petersson, Lennart Svensson

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2023

2022

Masked Autoencoders for Self-Supervised Learning on Automotive Point Clouds.

Georg Hess, Johan Jaxing, Elias Svensson, David Hagerman, Christoffer Petersson, Lennart Svensson

CoRR, 2022

Semi-supervised learning with natural language processing for right ventricle classification in echocardiography - a scalable approach.

Eva Hagberg, David Hagerman, Richard Johansson, Nasser Hosseini, Jan Liu, Elin Björnsson, Jennifer Alvén, Ola Hjelmgren

Comput. Biol. Medicine, 2022