Answer Set Programming (ASP) is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, FO(.), PDDL and many others. Since its first informal editions, ASP systems have been compared in the now well-established ASP Competition. The Third (Open) ASP Competition, as the sequel to the ASP...

Current logo retrieval research focuses on closed set scenarios. We argue that the logo domain is too large for this strategy and requires an open set approach. To foster research in this direction, a large-scale logo dataset, called Logos in the Wild, is collected and released to the public. A typical open set logo retrieval application is, for example, assessing the effectiveness of advertise...

This paper presents investigations into the performance of openset, text-independent speaker identification (OSTI-SI) under mismatched data conditions. The scope of the study includes attempts to reduce the adverse effects of such conditions through the introduction of a modified parallel model combination (PMC) method together with condition-adjusted T-Norm (CTNorm) into the OSTI-SI framework....

In this supplement, we provide we provide additional material to further the reader as understanding of the work on Open Set Deep Networks, Mean Activation Vectors, Open Set Recognition and OpenMax algorithm. We present additional experiments on ILSVRC 2012 dataset. First we present experiments to illustrate performance of OpenMax for various parameters of EVT calibration (Alg. 1, main paper) f...

The purpose of this paper is to introduce and study the concepts of fuzzy $e$-open set, fuzzy $e$-continuity and fuzzy $e$-compactness in intuitionistic fuzzy topological spaces. After giving the fundamental concepts of intuitionistic fuzzy sets and intuitionistic fuzzy topological spaces, we present intuitionistic fuzzy $e$-open sets and intuitionistic fuzzy $e$-continuity and other results re...

Abstract In this paper, we mainly intend to address the underwater image classification problem in an open-set scenario. Image algorithms have been mostly provided with a small set of species, while there exist lots species not available or even unknown ourselves. Thus, deal and extremely high false alarm rate real scenarios, especially case unseen species. Motivated by these challenges, our pr...