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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).
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).
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).
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.
