1 code implementation • 19 Mar 2024 • Raghavendra Selvan, Bob Pepin, Christian Igel, Gabrielle Samuel, Erik B Dam
The recent advances in deep learning (DL) have been accelerated by access to large-scale data and compute.
no code implementations • 12 Jan 2024 • Sumit Pandey, Satyasaran Changdar, Mathias Perslev, Erik B Dam
Automated segmentation of distinct tumor regions is critical for accurate diagnosis and treatment planning in pediatric brain tumors.
1 code implementation • 17 Mar 2023 • Raghavendra Selvan, Julian Schön, Erik B Dam
The resource consumption of deep learning models in terms of amount of training data, compute and energy costs are known to be massive.
no code implementations • 15 Sep 2021 • Raghavendra Selvan, Erik B Dam, Søren Alexander Flensborg, Jens Petersen
The performance of the proposed tensor network segmentation model is compared with relevant baseline methods.
1 code implementation • 13 Feb 2021 • Raghavendra Selvan, Erik B Dam, Jens Petersen
We use the matrix product state (MPS) tensor network on non-overlapping patches of a given input image to predict the segmentation mask by learning a pixel-wise linear classification rule in a high dimensional space.
1 code implementation • 13 Nov 2020 • Raghavendra Selvan, Silas Ørting, Erik B Dam
The recently introduced locally orderless tensor network (LoTeNet) for supervised image classification uses matrix product state (MPS) operations on grids of transformed image patches.