Constructing a semantic concept hierarchy covers only part of the problem in building any knowledgebased natural language processing (NLP) system: Language understanding requires mapping from syntactic structures into conceptual (i.e. interlingua) representation (henceforth verb-argument mapping), while language generation requires the inverse mapping. Jacobs [13] proposed a solution in which h...

We present a novel method for visual mapping and localization autonomous vehicles, by extracting, modeling, optimizing semantic road elements. Specifically, our integrates cascaded deep models to detect standardized elements instead of traditional point features, seek improved pose accuracy map representation compactness. To utilize the structural we model lights signs their representative keyp...

BACKGROUND Remote magnetic navigation-guided ablation with 3-dimensional (3D)-image integration could provide maximum benefit in patients with complex anatomy. We reviewed supraventricular tachycardia (SVT) ablation in adult patients with congenital heart disease to assess the contribution of these technologies. METHODS AND RESULTS One hundred fifty-four SVT ablation procedures (228 SVTs) usi...

Objective The aim of this study was to determine whether CARTO mapping is feasible in the right ventricle and assess its utility in guiding ablation of right ventricular outflow tract (RVOT) ventricualr tachycardia (VT). Background In patients with RVOT VT; CARTO mapping permits ablation guided by a VT complex, which may facilitate ablation of VT cases. However, the mapping system may be geomet...

Many works in the recent literature introduce semantic mapping methods that use CNNs (Convolutional Neural Networks) to recognize properties images. The types of (eg.: room size, place category, and objects) their classes kitchen bathroom, for category) are usually predefined restricted a specific task. Thus, all visual data acquired processed during construction maps lost only recognized remai...

In an endeavor to study natural systems at multiple spatial and taxonomic resolutions, there is urgent need for automated, high-throughput frameworks that can handle plethora of information. The coalescence remote-sensing, computer-vision, deep-learning elicits a new era in ecological research. However, complex systems, such as marine-benthic habitats, key processes still remain enigmatic due t...

In the current COVID-19 pandemic, people expect to use robots replace humans complete disinfection work in public places. Since different regions environment have risks, addition conventional SLAM capability, robot also needs be able recognize and distinguish objects scene customizable tasks. this paper, we propose a LiDAR-based semantic mapping system that can used for robotic By using prior i...

Performing collaborative semantic mapping is a critical challenge for cooperative robots to enhance their comprehensive contextual understanding of the surroundings. This article bridges gap between advances in geometry that relies on pure information fusion, and single robot focuses integrating continuous raw sensor data. In this article, novel hierarchical probabilistic framework proposed, wh...

In static analysis, approximation is typically encoded by abstract domains, providing systematic guidelines for specifying approximate semantic functions and precision assessments. However, it may well happen that an abstract domain contains redundant information for the specific purpose of approximating a given semantic function modeling some behavior of a system. This paper introduces Example...