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A graphics processing system that is operable to perform ray tracing using micromaps is disclosed. A tree representation of a micromap is generated, and when it is desired to determine whether and/or how a ray interacts with a sub-region of a primitive, the tree representation of the micromap is traversed to determine a property value for the sub-region of the primitive.
Line segments are powerful features complementary to points. They offer structural cues, robust to drastic viewpoint and illumination changes, and can be present even in texture-less areas. However, describing and matching them is more challenging compared to points due to partial occlusions, lack of texture, or repetitiveness. This paper introduces a new matching paradigm, where points, lines, an
In this paper we introduce the Tangent Sampson error, which is a generalization of the classical Sampson error in two-view geometry that allows for arbitrary central camera models. It only requires local gradients of the distortion map at the original correspondences (allowing for pre-computation) resulting in a negligible increase in computational cost when used in RANSAC or local refinement. The
In contrast to sparse keypoints, a handful of line segments can concisely encode the high-level scene layout, as they often delineate the main structural elements. In addition to offering strong geometric cues, they are also omnipresent in urban landscapes and indoor scenes. Despite their apparent advantages, current line-based reconstruction methods are far behind their point-based counterparts.
Software applications can be described using a computational model. These Models of Computation (MoCs) define rules governing application behaviour and properties that are enforced during execution. This thesis focuses on an actor-based MoC, known as dataflow-with-firing, where applications are modelled as actors connected by buffered channels. This model yields a concurrent application descriptio
This article provides a review of the application of stomatal frequency analysis to fossil leaves in the reconstruction of past atmospheric CO2 concentrations. It presents the physiological basis of the method, an overview of its application to leaves of Quaternary age, and an assessment of its potential and limitations. It also includes a description of the successive stages in a stomatal frequen
Combinatorial optimization is a powerful way to solve complex problems, like planning, scheduling, or hardware verification, by expressing the problem in a mathematical form using discrete variables that can be solved by general solvers. Due to major advances in algorithms for solving combinatorial optimization problems, these solvers can tackle real-world challenges efficiently. However, as solve
Sensitivity measures how much the output of an algorithm changes, in terms of Hamming distance, when part of the input is modified. While approximation algorithms with low sensitivity have been developed for many problems, no sensitivity lower bounds were previously known for approximation algorithms. In this work, we establish the first polynomial lower bound on the sensitivity of (randomized) ap
The transition to post-quantum cryptography is well underway. Driven by the recognition that Shor's algorithm would render all widely deployed asymmetric cryptosystems insecure in the presence of a sufficiently capable quantum computer, the cryptographic community has spent the past decade designing, evaluating, and standardizing a new generation of public-key primitives. In 2024, ML-KEM became th
Objective. This study aimed to investigate the potential of contrastive learning to improve auditory attention decoding (AAD) using electroencephalography (EEG) data in challenging cocktail-party scenarios with competing speech and background noise. Approach. Three different models were implemented for comparison: a baseline linear model (LM), a non-LM without contrastive learning (NLM), and a
The Hamming Quasi-Cyclic (HQC) key encapsulation mechanism (KEM), recently selected by NIST for standardization in the Post-Quantum Cryptography (PQC) process, distinguishes itself through its efficiency, robust design based on hard decoding problems in coding theory, and well-characterized decryption failure rates. Despite its selection, practical security concerns arise from implementation threa
Objective: Enhancing the reliability of myoelectric controllers that decode motor intent is a pressing challenge in the field of bionic prosthetics. State-of-the-art research has mostly focused on Supervised Learning (SL) techniques to tackle this problem. However, obtaining high-quality labeled data that accurately represents muscle activity during daily usage remains difficult. We investigate th
We study a network formation game where n players, identified with the nodes of a directed graph to be formed, choose where to wire their outgoing links in order to maximize their PageRank centrality. Specifically, the action of every player i consists in the wiring of a predetermined number di of directed out-links, and her utility is her own PageRank centrality in the network resulting from the
In this paper, we propose a scheme to identify discrete-time, multi-input/multi-output switched-linear systems (MIMO-SLSs) from input-output measurements. The key step is an observer-based transformation to a switched auto-regressive with exogenous input (SARX) model. This transformation converts the state-space (SS) identification problem into a MIMO-SARX identification problem by compressing in
Artificial intelligence (AI) and machine learning (ML) are rapidly permeating nearly every aspect of modern life, frompersonal devices and autonomous systems to industrial automation and environmental monitoring. The growing demandfor intelligence at the network edge is reshaping how computing hardware is conceived and built. Edge AI platforms areexpected to deliver high throughput within tight en
While the 8.2 ka abrupt cooling event is increasingly recognised as a major Holocene climatic anomaly, archaeological discussions of its cultural consequences have often been framed in terms of societal distress, including the collapse and abandonment of settlements. However, prehistoric communities must have responded in more diverse ways. This paper investigates the site-based socio-ecological a
Combinatorial optimization provides a powerful framework for solving complex optimization problems with general-purpose solvers by modelling the problem in an abstract language. Due to breakthroughs in algorithms to solve combinatorial optimization problems in last decades, combinatorial optimization has become a valid approach to solve many real world problems efficiently. Key application areas a
With the rapid growth of mobile communication systems, massive multiple-input multiple-output (MIMO) technology plays a key role in enhancing communication systems to meet growing data traffic demands. However, scaling the technology further challenges the system designers to balance design tradeoffs in order to provide efficient and low-cost communication systems. This requires efficient hardware
The first WARA Robotics Mobile Manipulation Challenge, held in December 2024 at ABB Corporate Research in Vasteras, Sweden, addressed the automation of task-intensive and repetitive manual labor in laboratory environments - specifically the transport and cleaning of glassware. Designed in collaboration with AstraZeneca, the challenge invited academic teams to develop autonomous robotic systems cap
