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   Articles with "learning multi" as a keyword



Fourth graders’ dyadic learning on multi-touch interfaces—versatile effects of verbalization prompts

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recommendations! Published in 2019 at "Educational Technology Research and Development"

DOI: 10.1007/s11423-018-9619-5

Abstract: Multi-touch interfaces allow for direct and simultaneous input by several co-present learners and afford hands-on learning experiences. Additional scaffolding for strategic behavior and/or verbalizations may constructively complement collaborative learning with a multi-touch device. In this… read more here.

Keywords: learning multi; touch interfaces; multi touch; verbalization prompts ... See more keywords

Beyond supervised learning: A multi-perspective approach to outpatient physical therapy mentoring

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recommendations! Published in 2018 at "Physiotherapy Theory and Practice"

DOI: 10.1080/09593985.2018.1443183

Abstract: ABSTRACT Background: Novice physical therapists face multiple challenges as they transition to autonomous, efficient, and seasoned therapists. Mentoring is known to facilitate growth among novice therapists; however, formalized mentoring programs within the outpatient setting are… read more here.

Keywords: beyond supervised; learning multi; program; supervised learning ... See more keywords

Deep Learning for Multi-User Proactive Beam Handoff: A 6G Application

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2023.3274810

Abstract: This paper demonstrates the use of deep learning and time series data generated from user equipment (UE) beam measurements and positions collected by the base station (BS) to enable handoffs between beams that belong to… read more here.

Keywords: learning multi; proactive beam; beam; beam handoff ... See more keywords

Learning Multi-Object Dense Descriptor for Autonomous Goal-Conditioned Grasping

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recommendations! Published in 2021 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2021.3062300

Abstract: In a goal-conditioned grasping task, a robot is asked to grasp the objects designated by a user. Existing methods for goal-conditioned grasping either can only handle relatively simple scenes or require extra user annotations. This… read more here.

Keywords: dense descriptor; conditioned grasping; learning multi; goal conditioned ... See more keywords

Learning Multi-Agent Coordination for Replenishment At Sea

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recommendations! Published in 2025 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2024.3518304

Abstract: Optimizing large-scale logistics is computationally challenging due to its scale and requirement to be robust to stochastic and time-varying weather disturbances. However, prior research in multi-agent reinforcement learning (MARL) does not address scenarios that capture… read more here.

Keywords: replenishment sea; multi agent; learning multi; agent coordination ... See more keywords

Learning Multi-Granularity Temporal Characteristics for Face Anti-Spoofing

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recommendations! Published in 2022 at "IEEE Transactions on Information Forensics and Security"

DOI: 10.1109/tifs.2022.3158062

Abstract: Face anti-spoofing (FAS) is essential for securing face recognition systems. Despite the decent performance, few existing works fully leverage temporal information. This would inevitably lead to inferior performance because real and fake faces tend to… read more here.

Keywords: multi granularity; face anti; granularity temporal; temporal characteristics ... See more keywords

Learning multi‐modal recurrent neural networks with target propagation

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recommendations! Published in 2024 at "Computational Intelligence"

DOI: 10.1111/coin.12691

Abstract: Modelling one‐to‐many type mappings in problems with a temporal component can be challenging. Backpropagation is not applicable to networks that perform discrete sampling and is also susceptible to gradient instabilities, especially when applied to longer… read more here.

Keywords: propagation; learning multi; recurrent neural; modal recurrent ... See more keywords

Integrating Machine Learning and Multi-Omics to Explore Neutrophil Heterogeneity

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recommendations! Published in 2025 at "Biomedicines"

DOI: 10.3390/biomedicines13092171

Abstract: Traditionally considered as homogeneous innate immune cells, neutrophils are now found to exhibit phenotypic and functional heterogeneity. How to determine whether the functional changes of neutrophils are caused by activation or the result of gene… read more here.

Keywords: learning multi; neutrophil heterogeneity; multi omics; machine learning ... See more keywords