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Additional file 2 of Reviewing the availability, efficacy and clinical utility of Telepsychology in dialectical behavior therapy (Tele-DBT) ...
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Reviewing the availability, efficacy and clinical utility of Telepsychology in dialectical behavior therapy (Tele-DBT) ...
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Reviewing the availability, efficacy and clinical utility of Telepsychology in dialectical behavior therapy (Tele-DBT) ...
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Transregional News Media Coverage in Multilingual Countries: The Impact of Market Size, Source, and Media Type in Switzerland ...
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Issues in Machine Translation of Indian Languages for Information Retrieval ...
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Issues in Machine Translation of Indian Languages for Information Retrieval ...
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Transregional News Media Coverage in Multilingual Countries: The Impact of Market Size, Source, and Media Type in Switzerland ...
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Natural-Language Multi-Agent Simulations of Argumentative Opinion Dynamics ...
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Proceedings Eighteenth Conference on Theoretical Aspects of Rationality and Knowledge ...
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Exploiting Natural Language for Efficient Risk-Aware Multi-robot SaR Planning ...
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Abstract:
The ability to develop a high-level understanding of a scene, such as perceiving danger levels, can prove valuable in planning multi-robot search and rescue (SaR) missions. In this work, we propose to uniquely leverage natural language descriptions from the mission commander in chief and image data captured by robots to estimate scene danger. Given a description and an image, a state-of-the-art deep neural network is used to assess a corresponding similarity score, which is then converted into a probabilistic distribution of danger levels. Because commonly used visio-linguistic datasets do not represent SaR missions well, we collect a large-scale image-description dataset from synthetic images taken from realistic disaster scenes and use it to train our machine learning model. A risk-aware variant of the Multi-robot Efficient Search Path Planning (MESPP) problem is then formulated to use the danger estimates in order to account for high-risk locations in the environment when planning the searchers' paths. ... : 8 pages, 5 figures. To be presented at the IEEE International Conference on Robotics and Automation, 2021. Dataset available at: https://github.com/vikshree/DISC-L.git ...
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Keyword:
FOS Computer and information sciences; Human-Computer Interaction cs.HC; Multiagent Systems cs.MA; Robotics cs.RO
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URL: https://arxiv.org/abs/2104.03809 https://dx.doi.org/10.48550/arxiv.2104.03809
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VocalGeo: Using Speech to Provide Geospatial Context in the Classroom ...
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VocalGeo: Using Speech to Provide Geospatial Context in the Classroom ...
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Unsupervised Morphological Segmentation and Part-of-Speech Tagging for Low-Resource Scenarios ...
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Multi-lingual agents through multi-headed neural networks ...
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Prediction of antimicrobial peptides toxicity based on their physico-chemical properties using machine learning techniques ...
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A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain ...
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Prediction of antimicrobial peptides toxicity based on their physico-chemical properties using machine learning techniques ...
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A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain ...
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