Search Results for author: Joakim Bruslund Haurum

Found 10 papers, 8 papers with code

An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders

1 code implementation4 Jun 2024 Scott C. Lowe, Joakim Bruslund Haurum, Sageev Oore, Thomas B. Moeslund, Graham W. Taylor

Our suite of benchmarking experiments use encoders pretrained solely on ImageNet-1k with either supervised or self-supervised training techniques, deployed on image datasets that were not seen during training, and clustered with conventional clustering algorithms.

Benchmarking Clustering

BarcodeBERT: Transformers for Biodiversity Analysis

1 code implementation4 Nov 2023 Pablo Millan Arias, Niousha Sadjadi, Monireh Safari, ZeMing Gong, Austin T. Wang, Scott C. Lowe, Joakim Bruslund Haurum, Iuliia Zarubiieva, Dirk Steinke, Lila Kari, Angel X. Chang, Graham W. Taylor

Understanding biodiversity is a global challenge, in which DNA barcodes - short snippets of DNA that cluster by species - play a pivotal role.

Model Selection

Which Tokens to Use? Investigating Token Reduction in Vision Transformers

1 code implementation9 Aug 2023 Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund

While different methods have been explored to achieve this goal, we still lack understanding of the resulting reduction patterns and how those patterns differ across token reduction methods and datasets.

Classification Token Reduction

MOTCOM: The Multi-Object Tracking Dataset Complexity Metric

no code implementations20 Jul 2022 Malte Pedersen, Joakim Bruslund Haurum, Patrick Dendorfer, Thomas B. Moeslund

There exists no comprehensive metric for describing the complexity of Multi-Object Tracking (MOT) sequences.

Multi-Object Tracking Object

Sewer-ML: A Multi-Label Sewer Defect Classification Dataset and Benchmark

1 code implementation CVPR 2021 Joakim Bruslund Haurum, Thomas B. Moeslund

To this end, in this work we present a large novel and publicly available multi-label classification dataset for image-based sewer defect classification called Sewer-ML.

Classification General Classification +2

Cannot find the paper you are looking for? You can Submit a new open access paper.