Raghavendra Selvan

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Københavns Uni

https://raghavian.github.io/

Segmenting two-dimensional structures with strided tensor networks

Tensor networks provide an efficient approximation of operations involvi...
02/13/2021 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Dynamic β-VAEs for quantifying biodiversity by clustering optically recorded insect signals

While insects are the largest and most diverse group of animals, constit...
02/10/2021 ∙ by Klas Rydhmer, et al. ∙ 0 ∙ share

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Detection of foraging behavior from accelerometer data using U-Net type convolutional networks

Narwhal is one of the most mysterious marine mammals, due to its isolate...
01/06/2021 ∙ by Manh Cuong Ngô, et al. ∙ 0 ∙ share

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Multi-layered tensor networks for image classification

The recently introduced locally orderless tensor network (LoTeNet) for s...
11/13/2020 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Locally orderless tensor networks for classifying two- and three-dimensional medical images

Tensor networks are factorisations of high rank tensors into networks of...
09/25/2020 ∙ by Raghavendra Selvan, et al. ∙ 10 ∙ share

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Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models

Deep learning (DL) can achieve impressive results across a wide variety ...
07/06/2020 ∙ by Lasse F. Wolff Anthony, et al. ∙ 22 ∙ share

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Uncertainty quantification in medical image segmentation with Normalizing Flows

Medical image segmentation is inherently an ambiguous task due to factor...
06/04/2020 ∙ by Raghavendra Selvan, et al. ∙ 15 ∙ share

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Lung Segmentation from Chest X-rays using Variational Data Imputation

Pulmonary opacification is the inflammation in the lungs caused by many ...
05/20/2020 ∙ by Raghavendra Selvan, et al. ∙ 14 ∙ share

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Tensor Networks for Medical Image Classification

With the increasing adoption of machine learning tools like neural netwo...
04/21/2020 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs

We present an end-to-end deep learning segmentation method by combining ...
08/22/2019 ∙ by Antonio Garcia-Uceda Juarez, et al. ∙ 0 ∙ share

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Segmentation of Roots in Soil with U-Net

Plant root research can provide a way to attain stress-tolerant crops th...
02/28/2019 ∙ by Abraham George Smith, et al. ∙ 0 ∙ share

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Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks

Graph refinement, or the task of obtaining subgraphs of interest from ov...
11/21/2018 ∙ by Raghavendra Selvan, et al. ∙ 10 ∙ share

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Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses

In this work, we adapt a method based on multiple hypothesis tracking (M...
06/23/2018 ∙ by Raghavendra Selvan, et al. ∙ 2 ∙ share

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Extraction of Airways using Graph Neural Networks

We present extraction of tree structures, such as airways, from image da...
04/12/2018 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Mean Field Network based Graph Refinement with application to Airway Tree Extraction

We present tree extraction in 3D images as a graph refinement task, of o...
04/10/2018 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing

Segmenting tree structures is common in several image processing applica...
08/07/2017 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Extraction of airway trees using multiple hypothesis tracking and template matching

Knowledge of airway tree morphology has important clinical applications ...
11/24/2016 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Raghavendra Selvan

Featured Co-authors

Max Welling

Marleen de Bruijne

Jens Petersen

Akshay Pai

Mads Nielsen

Thomas Kipf

Erik B Dam

Jesper H. Pedersen

Silas Ørting

Antonio Garcia-Uceda Juarez

Abraham George Smith

Segmenting two-dimensional structures with strided tensor networks

Dynamic β-VAEs for quantifying biodiversity by clustering optically recorded insect signals

Detection of foraging behavior from accelerometer data using U-Net type convolutional networks

Multi-layered tensor networks for image classification

Locally orderless tensor networks for classifying two- and three-dimensional medical images

Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models

Uncertainty quantification in medical image segmentation with Normalizing Flows

Lung Segmentation from Chest X-rays using Variational Data Imputation

Tensor Networks for Medical Image Classification

A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs

Segmentation of Roots in Soil with U-Net

Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks

Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses

Extraction of Airways using Graph Neural Networks

Mean Field Network based Graph Refinement with application to Airway Tree Extraction

Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing

Extraction of airway trees using multiple hypothesis tracking and template matching