SDF-SLAM: Semantic Depth Filter SLAM for Dynamic Environments
IEEE Access, 2020 Simultaneous Localization and Mapping (SLAM) has been widely applied in computer vision and robotics. For the dynamic environments which are very common in the real word, traditional visual SLAM system faces significant drop in localization and mapping ...
Linyan Cui, Chaowei Ma
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Visual SLAM Based on Semantic Segmentation and Geometric Constraints for Dynamic Indoor Environments
IEEE Access, 2022 Simultaneous localization and mapping (SLAM), a core technology of mobile robots and autonomous driving, has received more and more attention in recent years.
Shiqiang Yang +5 more
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A Semantic Survey on Modal Verbs in Todays' Persian Language from a Typological Point of View [PDF]
نشریه پژوهشهای زبانشناسی, 2021 This study aimed at investigating the semantic aspect of modal verbs in today’s Persian language from a typological perspective, which provided us with an opportunity to compare the meanings of Persian modal verbs with those of the other languages.
Shahla Sharifi, Narjes Banou Sabouri
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AI Technologies for Machine Supervision and Help in a Rehabilitation Scenario
Multimodal Technologies and Interaction, 2022 We consider, evaluate, and develop methods for home rehabilitation scenarios. We show the required modules for this scenario. Due to the large number of modules, the framework falls into the category of Composite AI. Our work is based on collected videos
Gábor Baranyi +9 more
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Semantic Mapping for Mobile Robots in Indoor Scenes: A Survey
Information, 2021 Sensing and mapping its surroundings is an essential requirement for a mobile robot. Geometric maps endow robots with the capacity of basic tasks, e.g., navigation.
Xiaoning Han +3 more
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SemAttNet: Toward Attention-Based Semantic Aware Guided Depth Completion
IEEE Access, 2022 Depth completion involves recovering a dense depth map from a sparse map and an RGB image. Recent approaches focus on utilizing color images as guidance images to recover depth at invalid pixels.
Danish Nazir +4 more
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Indoor 3D Semantic Robot VSLAM Based on Mask Regional Convolutional Neural Network
IEEE Access, 2020 During the construction of indoor environmental semantic maps by robot Vision SLAM (VSLAM), there exist some problems such as low label classification accuracy and low precision under the situation of sparse feature points.
Chongben Tao +4 more
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Lexical typology through similarity semantics: Toward a semantic map of motion verbs [PDF]
, 2012 This paper discusses a multidimensional probabilistic semantic map of lexical motion verb stems based on data collected from parallel texts (viz. translations of the Gospel according to Mark) for 100 languages from all continents.
Wälchli, Bernhard +4 more
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A visual questioning answering approach to enhance robot localization in indoor environments
Frontiers in Neurorobotics, 2023 Navigating robots with precision in complex environments remains a significant challenge. In this article, we present an innovative approach to enhance robot localization in dynamic and intricate spaces like homes and offices. We leverage Visual Question
Juan Diego Peña-Narvaez +3 more
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Semantic Map Geometry: Two Approaches
Linguistic Discovery, 2010 This paper discusses two ways in which the geometry of a semantic map can be defined: on the basis of a set of cross-linguistic data or on the basis of a semantic analysis of the meanings involved. I will argue that under a purely ?data-driven?
Joost Zwarts
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