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Ett smartare Sverige Sacos kongress 2025 Motioner och styrelsens yttranden 1/59 Motioner och styrelsens yttranden Innehåll Angående motioner och styrelsens yttranden ................................................................................. 2 Motion 1: Förteckning av nomineringar ........................................................................................... 3 Motion 2: Tydliggö
With the increasing number of IoT devices deployed, the problem of switching ownership of devices is becoming more apparent. Especially, there is a need for transfer protocols not only addressing a single unit ownership transfer but secure transfer of a complete infrastructure of IoT units including also resource constraint devices. In this paper we present our novel ownership transfer protocol fo
HQC is an IND-CCA2 KEM running for standardization in NIST’s post-quantum cryptography project and has advanced to the second round. It is a code-based scheme in the class of public key encryptions, with given sets of parameters spanning NIST security strength 1, 3 and 5, corresponding to 128, 192 and 256 bits of classic security.In this paper we present an attack recovering the secret key of an H
Understanding 3d human interactions is fundamental for fine grained scene analysis and behavioural modeling. However, most of the existing models focus on analyzing a single person in isolation, and those who process several people focus largely on resolving multi-person data association, rather than inferring interactions. This may lead to incorrect, lifeless 3d estimates, that miss the subtle hu
In this paper, we study the minimal problem of estimating the essential matrix between two cameras with constant but unknown focal length and radial distortion. This problem is of both theoretical and practical interest and it has not been solved previously. We have derived a fast and stable polynomial solver based on Gr{\"o}bner basis method. This solver enables simultaneous auto-calibration of f
Popular Abstract in Swedish Ett varmare klimat ökar generellt risken för angrepp av skadeinsekter på jordbruksgrödor, och många skadeinsekter förväntas sprida sig norrut. Den här avhandlingen fokuserar på hur ett varmare klimat kan påverka koloradoskalbaggen, en allvarlig skadegörare i potatisodlingar. Koloradoskalbaggen kom från Mexiko till Europa i början av 1900-talet, och har sedan dess spridiEuropean agriculture is facing the challenge of managing the impact of climate change on food security. Agriculture in a northern temperate climate is likely to benefit from higher temperature and longer growing season while, in the south, crop productivity is likely to decline. Such changes in climate could also affect the population dynamics of insect pests. The Colorado potato beetle (CPB) is o
Many computer vision applications require robust estimation of the underlying geometry, in terms of camera motion and 3D structure of the scene. These robust methods often rely on running minimal solvers in a RANSAC framework. In this paper we show how we can make polynomial solvers based on the action matrix method faster, by careful selection of the monomial bases. These monomial bases have trad
To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization. In most of existing camera pose estimation solvers, the principal point is assumed to be in the image center. Unfortunately, this assumption is not always true, especially for asymmetrically cropped images. In this paper, w
This paper introduces the first minimal solvers that jointly solve for affine-rectification and radial lens distortion from coplanar repeated patterns. Even with imagery from moderately distorted lenses, plane rectification using the pinhole camera model is inaccurate or invalid. The proposed solvers incorporate lens distortion into the camera model and extend accurate rectification to wide-angle
The problem of graph matching under node and pairwise constraints is fundamental in areas as diverse as combinatorial optimization, machine learning or computer vision, where representing both the relations between nodes and their neighborhood structure is essential. We present an end-to-end model that makes it possible to learn all parameters of the graph matching process, including the unary and
We introduce new, fine-grained action and emotion recognition tasks defined on non-staged videos, recorded during robot-assisted therapy sessions of children with autism. The tasks present several challenges: a large dataset with long videos, a large number of highly variable actions, children that are only partially visible, have different ages and may show unpredictable behaviour, as well as non
We propose drl-RPN, a deep reinforcement learning-based visual recognition model consisting of a sequential region proposal network (RPN) and an object detector. In contrast to typical RPNs, where candidate object regions (RoIs) are selected greedily via class-agnostic NMS, drl-RPN optimizes an objective closer to the final detection task. This is achieved by replacing the greedy RoI selection pro
In this paper we explore the role of duality principles within the problem of rotation averaging, a fundamental task in a wide range of computer vision applications. In its conventional form, rotation averaging is stated as a minimization over multiple rotation constraints. As these constraints are non-convex, this problem is generally considered challenging to solve globally. We show how to circu
In the last decade, museums that were established in the 20th century by immigrants from the five Nordic countries have become increasingly concerned with broadening their audiences and more actively engaging their visitors. Efforts to do this have varied from offering traveling exhibitions produced in the Nordic countries, film programs, festivals, concert series, cocktail hours, culinary confere
Neural networks designed for real-time object detectionhave recently improved significantly, but in practice, look-ing at only a single RGB image at the time may not be ideal.For example, when detecting objects in videos, a foregrounddetection algorithm can be used to obtain compact temporaldata, which can be fed into a neural network alongside RGBimages. We propose an approach for doing this, bas
This chapter is devoted to modeling and optimization techniques applicable to communication network design and planning. The main emphasis is put on the models dealing with optimization of the capacity of network resources and traffic routing that lead to tractable optimization problems. It is a common belief that the right means for such modeling are multicommodity flow networks (MFN). MFN form a
Local blood flow in the thigh was measured with 133Xe clearance technique in eight male distance runners after compression with a foam rubber compress and a standard elastic bandage. Two degrees of compression were tested, and an initial experiment with rested subjects was followed by a similar experiment immediately after running. Maximum compression exerted a cutaneous pressure of 85 (+/- 8) mm
