| 1. |
- Gu, Xuan, 1988-, et al.
(författare)
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Generating Diffusion MRI Scalar Maps from T1 Weighted Images Using Generative Adversarial Networks
- 2019
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Ingår i: Image Analysis - 21st Scandinavian Conference, SCIA 2019, Proceedings. - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783030202040 - 9783030202057 ; 11482 LNCS, s. 489-498
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Konferensbidrag (refereegranskat)abstract
- Diffusion magnetic resonance imaging (diffusion MRI) is a non-invasive microstructure assessment technique. Scalar measures, such as FA (fractional anisotropy) and MD (mean diffusivity), quantifying micro-structural tissue properties can be obtained using diffusion models and data processing pipelines. However, it is costly and time consuming to collect high quality diffusion data. Here, we therefore demonstrate how Generative Adversarial Networks (GANs) can be used to generate synthetic diffusion scalar measures from structural T1-weighted images in a single optimized step. Specifically, we train the popular CycleGAN model to learn to map a T1 image to FA or MD, and vice versa. As an application, we show that synthetic FA images can be used as a target for non-linear registration, to correct for geometric distortions common in diffusion MRI.
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| 2. |
- Bylow, Erik, et al.
(författare)
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Combining Depth Fusion and Photometric Stereo for Fine-Detailed 3D Models
- 2019
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Ingår i: Image Analysis - 21st Scandinavian Conference, SCIA 2019, Proceedings. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783030202040 ; 11482 LNCS, s. 261-274
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Konferensbidrag (refereegranskat)abstract
- In recent years, great progress has been made on the problem of 3D scene reconstruction using depth sensors. On a large scale, these reconstructions look impressive, but often many fine details are lacking due to limitations in the sensor resolution. In this paper we combine two well-known principles for recovery of 3D models, namely fusion of depth images with photometric stereo to enhance the details of the reconstructions. We derive a simple and transparent objective functional that takes both the observed intensity images and depth information into account. The experimental results show that many details are captured that are not present in the input depth images. Moreover, we provide a quantitative evaluation that confirms the improvement of the resulting 3D reconstruction using a 3D printed model.
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| 3. |
- Flood, Gabrielle, et al.
(författare)
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Efficient Merging of Maps and Detection of Changes
- 2019
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Ingår i: Image Analysis - 21st Scandinavian Conference, SCIA 2019, Proceedings. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783030202040 ; 11482 LNCS, s. 348-360
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Konferensbidrag (refereegranskat)abstract
- With the advent of cheap sensors and computing capabilities as well as better algorithms it is now possible to do structure from motion using crowd sourced data. Individual estimates of a map can be obtained using structure from motion (SfM) or simultaneous localization and mapping (SLAM) using e.g. images, sound or radio. However the problem of map merging as used for collaborative SLAM needs further attention. In this paper we study the basic principles behind map merging and collaborative SLAM. We develop a method for merging maps – based on a small memory footprint representation of individual maps – in a way that is computationally efficient. We also demonstrate how the same framework can be used to detect changes in the map. This makes it possible to remove inconsistent parts before merging the maps. The methods are tested on both simulated and real data, using both sensor data from radio sensors and from cameras.
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| 4. |
- Li, Zhongguo, et al.
(författare)
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Parametric Model-Based 3D Human Shape and Pose Estimation from Multiple Views
- 2019
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Ingår i: Image Analysis - 21st Scandinavian Conference, SCIA 2019, Proceedings. - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783030202040 ; 11482 LNCS, s. 336-347
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Konferensbidrag (refereegranskat)abstract
- Human body pose and shape estimation is an important and challenging task in computer vision. This paper presents a novel method for estimating 3D human body pose and shape from several RGB images, using detected joint positions in the images and based on a parametric human body model. Firstly, the 2D joint points of the RGB images are estimated using a deep neural network, which provides a strong prior on the pose. Then, an energy function is constructed based on the 2D joint points in the RGB images and a parametric human body model. By minimizing the energy function, the pose, shape and camera parameters are obtained. The main contribution of the method over previous work, is that the optimization is based on several images simultaneously using only estimated joint positions in the images. We have performed experiments on both synthetic and real image data-sets, that demonstrate that our method can reconstruct 3D human bodies with better accuracy than previous single view methods.
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| 5. |
- Persson, Patrik, et al.
(författare)
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Global Trifocal Adjustment
- 2019
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Ingår i: Image Analysis - 21st Scandinavian Conference, SCIA 2019, Proceedings. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783030202040 ; 11482 LNCS, s. 287-298
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Konferensbidrag (refereegranskat)abstract
- In this paper we introduce a fast and robust structure-less alternative to full bundle adjustment. The method is based on optimizing algebraic errors for trilinear constraints from triplets of views. It is shown that the error generated by a triplet of views can be described by a fixed triangular matrix regardless of the number of feature correspondences between the views. The method has been evaluated on various real and synthetic datasets and shows good convergence properties with a large convergence basin and solutions that are close to the optimal solution. The method has been compared to Global Epipolar Adjustment, GEA, which is based on the bilinear constraint. It will be shown that the method can handle the degenerate configurations of GEA.
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| 6. |
- Cheraghchi, M., et al.
(författare)
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Approximating Linear Threshold Predicates
- 2010
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Ingår i: Lecture Notes in Computer Science. 13th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2010 and 14th International Workshop on Randomization and Computation, RANDOM 2010, Barcelona, 1-3 September 2010. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 9783642153686 ; 6302, s. 110-123
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Konferensbidrag (refereegranskat)abstract
- We study constraint satisfaction problems on the domain {-1,1}, where the given constraints are homogeneous linear threshold predicates. That is, predicates of the form sgn(w1 x1+⋯+wn x n ) for some positive integer weights w 1, ..., w n . Despite their simplicity, current techniques fall short of providing a classification of these predicates in terms of approximability. In fact, it is not easy to guess whether there exists a homogeneous linear threshold predicate that is approximation resistant or not. The focus of this paper is to identify and study the approximation curve of a class of threshold predicates that allow for non-trivial approximation. Arguably the simplest such predicate is the majority predicate sgn(x 1+⋯+xn ), for which we obtain an almost complete understanding of the asymptotic approximation curve, assuming the Unique Games Conjecture. Our techniques extend to a more general class of "majority-like" predicates and we obtain parallel results for them. In order to classify these predicates, we introduce the notion of Chow-robustness that might be of independent interest.
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| 7. |
- Hedin, Daniel, 1978, et al.
(författare)
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A Principled Approach to Tracking Information Flow in the Presence of Libraries
- 2017
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Berlin, Heidelberg : Springer Berlin Heidelberg. - 1611-3349 .- 0302-9743. - 9783662544549 ; 10204, s. 49-70
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Konferensbidrag (refereegranskat)abstract
- There has been encouraging progress on information flow control for programs in increasingly complex programming languages, tracking the propagation of information from input sources to output sinks. Yet, programs are typically deployed in an environment with rich APIs and powerful libraries, posing challenges for information flow control when the code for these APIs and libraries is either unavailable or written in a different language.This paper presents a principled approach to tracking information flow in the presence of libraries. With the goal to strike the balance between security and precision, we present a framework that explores the middle ground between the “shallow”, signature-based modeling of libraries and the “deep”, stateful approach, where library models need to be supplied manually. We formalize our approach for a core language, extend it with lists and higher-order functions, and establish soundness results with respect to the security condition of noninterference.
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| 8. |
- Isaksson, Martin, et al.
(författare)
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Adaptive Expert Models for Federated Learning
- 2023
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Ingår i: <em>Lecture Notes in Computer Science </em>Volume 13448 Pages 1 - 16 2023. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783031289958 ; 13448 LNAI, s. 1-16
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Konferensbidrag (refereegranskat)abstract
- Federated Learning (FL) is a promising framework for distributed learning when data is private and sensitive. However, the state-of-the-art solutions in this framework are not optimal when data is heterogeneous and non-IID. We propose a practical and robust approach to personalization in FL that adjusts to heterogeneous and non-IID data by balancing exploration and exploitation of several global models. To achieve our aim of personalization, we use a Mixture of Experts (MoE) that learns to group clients that are similar to each other, while using the global models more efficiently. We show that our approach achieves an accuracy up to 29.78% better than the state-of-the-art and up to 4.38% better compared to a local model in a pathological non-IID setting, even though we tune our approach in the IID setting. © 2023, The Author(s)
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| 9. |
- Smirnova, Oxana, et al.
(författare)
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The NorduGrid Architecture And Middleware for Scientific Applications
- 2003
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Ingår i: Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer Berlin Heidelberg. ; 2657, s. 264-273
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The NorduGrid project operates a production Grid infrastructure in Scandinavia and Finland using own innovative middleware solutions. The resources range from small test clusters at academic institutions to large farms at several supercomputer centers, a
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| 10. |
- Aanæs, Henrik, et al.
(författare)
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Camera Resectioning from a Box
- 2009
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Ingår i: Lecture Notes in Computer Science. - 0302-9743 .- 1611-3349.
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Konferensbidrag (refereegranskat)abstract
- In this paper we describe how we can do camera resectioning from a box with unknown dimensions, i.e. determine the camera model, assuming that image pixels are square. This assumption is equivalent to assuming that the camera as an aspect ratio of one and zero skew, and holds for most - if not all - digital cameras. Our proposed method works by first deriving 9 linear constraints on the projective camera matrix from the box, leaving a 3 dimensional subspace in which the projective camera matrix can lye. A single solution in this 3D subspace is then found via a method by Triggs in 1999, which uses the squared pixel assumption to set up a 4th degree polynomial to which the solution is the desired model. This approach is, however, numerically challenging, and we use several means to combat this issue. Lastly the solution is refined in an iterative manner, i.e. using bundle adjustment.
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