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Outputs (216)

Eliminating the Dreaded Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery (2018)
Presentation / Conference Contribution
Payen de La Garanderie, G., Atapour-Abarghouei, A., & Breckon, T. (2018, September). Eliminating the Dreaded Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery. Presented at 15th European Conference on Computer Vision (ECCV 2018), Munich, Germany

Recent automotive vision work has focused almost exclusively on processing forward-facing cameras. However, future autonomous vehicles will not be viable without a more comprehensive surround sensing, akin to a human driver, as can be provided by 360... Read More about Eliminating the Dreaded Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery.

A Multi-Core Ready Discrete Element Method With Triangles Using Dynamically Adaptive Multiscale Grids (2018)
Journal Article
Krestenitis, K., & Weinzierl, T. (2019). A Multi-Core Ready Discrete Element Method With Triangles Using Dynamically Adaptive Multiscale Grids. Concurrency and Computation: Practice and Experience, 31(19), Article e4935. https://doi.org/10.1002/cpe.4935

The simulation of vast numbers of rigid bodies of non‐analytical shapes and of tremendously different sizes that collide with each other is computationally challenging. A bottleneck is the identification of all particle contact points per time step.... Read More about A Multi-Core Ready Discrete Element Method With Triangles Using Dynamically Adaptive Multiscale Grids.

Consistency for counting quantifiers (2018)
Presentation / Conference Contribution
Madelaine, F., & Martin, B. (2018, August). Consistency for counting quantifiers. Presented at 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018)., Liverpool, UK

We apply the algebraic approach for Constraint Satisfaction Problems (CSPs) with counting quantifiers, developed by Bulatov and Hedayaty, for the first time to obtain classifications for computational complexity. We develop the consistency approach f... Read More about Consistency for counting quantifiers.

The complexity of disjunctive linear Diophantine constraints (2018)
Presentation / Conference Contribution
Bodirsky, M., Mamino, M., Martin, B., & Mottet, A. (2018, August). The complexity of disjunctive linear Diophantine constraints. Presented at 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018)., Liverpool, UK

We study the Constraint Satisfaction Problem CSP( A), where A is first-order definable in (Z;+,1) and contains +. We prove such problems are either in P or NP-complete.

Simple games versus weighted voting games (2018)
Presentation / Conference Contribution
Hof, F., Kern, W., Kurz, S., & Paulusma, D. (2018, September). Simple games versus weighted voting games. Presented at 11th International Symposium on Algorithmic Game Theory (SAGT 2018)., Beijing, China

A simple game (N, v) is given by a set N of n players and a partition of 2N into a set L of losing coalitions L with value v(L)=0 that is closed under taking subsets and a set W of winning coalitions W with v(W)=1 . Simple games with α=minp≥0maxW∈W,L... Read More about Simple games versus weighted voting games.

Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses (2018)
Presentation / Conference Contribution
Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018, August). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund, Sweden

Whilst a high dropout rate is a well-known problem in MOOCs, few studies take a data-driven approach to understand the reasons of such a phenomenon, and to thus be in the position to recommend and design possible adaptive solutions to alleviate it. I... Read More about Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses.

Binary search in graphs revisited (2018)
Journal Article
Deligkas, A., Mertzios, G., & Spirakis, P. (2019). Binary search in graphs revisited. Algorithmica, 81(5), Article 1757. https://doi.org/10.1007/s00453-018-0501-y

In the classical binary search in a path the aim is to detect an unknown target by asking as few queries as possible, where each query reveals the direction to the target. This binary search algorithm has been recently extended by Emamjomeh-Zadeh et... Read More about Binary search in graphs revisited.

3D Sketching in Virtual Reality for immersive model search (2018)
Presentation / Conference Contribution
Giunchi, D., James, S., & Steed, A. (2028, August). 3D Sketching in Virtual Reality for immersive model search. Presented at Expressive '18: Joint Symposium on Computational Aesthetics and Sketch-Based Interfaces and Modeling and Non-Photorealistic Animation and Rendering, Victoria, BC, Canada

We describe a novel method for searching 3D model collections using free-form sketches within a virtual environment as queries. As opposed to traditional sketch retrieval, our queries are drawn directly onto an example model. Using immersive virtual... Read More about 3D Sketching in Virtual Reality for immersive model search.