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Found 8 papers, 0 papers with code
Coronary Artery Segmentation from Intravascular Optical Coherence Tomography Using Deep Capsules
We show that our developments lead to a model, DeepCap, that is on par with state-of-the-art machine learning methods in terms of segmentation quality and robustness, while using as little as 12% of the parameters.
Answer Set Programming Modulo `Space-Time'
We present ASP Modulo `Space-Time', a declarative representational and computational framework to perform commonsense reasoning about regions with both spatial and temporal components.
Visual Explanation by High-Level Abduction: On Answer-Set Programming Driven Reasoning about Moving Objects
We present the formal framework, its general implementation as a (declarative) method in answer set programming, and an example application and evaluation based on two diverse video datasets: the MOTChallenge benchmark developed by the vision community, and a recently developed Movie Dataset.
Deeply Semantic Inductive Spatio-Temporal Learning
We present an inductive spatio-temporal learning framework rooted in inductive logic programming.
Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories
We present ASPMT(QS), a novel approach and fully-implemented prototype for non-monotonic spatial reasoning -a crucial requirement within dynamic spatial systems- based on Answer Set Programming Modulo Theories (ASPMT).
ASPMT(QS): Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories
We present ASPMT(QS), a novel approach and fully-implemented prototype for non-monotonic spatial reasoning ---a crucial requirement within dynamic spatial systems-- based on Answer Set Programming Modulo Theories (ASPMT).
Spatial Symmetry Driven Pruning Strategies for Efficient Declarative Spatial Reasoning
Declarative spatial reasoning denotes the ability to (declaratively) specify and solve real-world problems related to geometric and qualitative spatial representation and reasoning within standard knowledge representation and reasoning (KR) based methods (e. g., logic programming and derivatives).
Cognitive Interpretation of Everyday Activities: Toward Perceptual Narrative Based Visuo-Spatial Scene Interpretation
We position a narrative-centred computational model for high-level knowledge representation and reasoning in the context of a range of assistive technologies concerned with "visuo-spatial perception and cognition" tasks.
